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  • Tweak Conky Layout via a script

    - by begtognen
    I'm using a script in Conky in order to display my new gmail on my desktop. It works beautifully, but is kind of ugly, and I'm not sure how to fix it. What I've currently got looks like this: And what I'd like is this: Any ideas for how to make that happen are much appreciated. Here's the script I'm currently using (I think I've snipped out the correct part, if I haven't please let me know.) #!/usr/bin/perl use Switch; use Text::Wrap; my $what=$ARGV[0]; $user="username"; #username for gmail account $pass="password"; #password for gmail account $file="/tmp/gmail.html"; #temporary file to store gmail #wrap format for subject $Text::Wrap::columns=65; #Number of columns to wrap subject at $initial_tab=""; #Tab for first line of subject $subsequent_tab="\t"; #tab for wrapped lines $quote="\""; #put quotes around subject #limit the number of emails to be displayed $emails=-1; #if -1 display all emails &passwd; #give password the proper url character encoding switch($what){ #determine what the user wants case "n" {&gmail; print "$new\n";} #print number of new emails case "s" { #print $from and $subj for new email &gmail; if ($new0){ my $size=@from; if ($emails!=-1 && $size$emails){$size=$emails;} #limit number of emails displayed for(my $i=0; $i$emails){print "$emails out of $size new emails displayed\n";} } } case "e" { #print number of new emails, $from, and $subj &gmail; if($new==0){print "You have no new emails.\n";} else{ print "You have $new new email(s).\n"; my $size=@from; if ($emails!=-1 && $size$emails){$size=$emails;} #limit number of emails displayed for(my $i=0; $i$emails){print "$emails out of $size new emails displayed\n";} } } else { print "Usage Error: gmail.pl \n"; print "\tn displays number of new emails\n"; print "\ts displays from line and subject line for each new email.\n"; print "\te displays the number of new emails and from line plus \n"; print "\t\tsubject line for each new email.\n"; } #didn't give proper option } sub gmail{ if(!(-e $file)){ #create file if it does not exists `touch $file`; } #get new emails `wget -O - https://$user:$pass\@mail.google.com/mail/feed/atom --no-check-certificate $file`; open(IN, $file); #open $file my $i=0; #initialize count $new=0; #initialize new emails to 0 my $flag=0; while(){ #cycle through $file if(//){$flag=1;} elsif(/(\d+)/){$new=$1;} #grab number of new emails elsif($flag==1){ if(/.+/){push(@subj, &msg);} #grab new email titles elsif(/(.+)/){push(@from, $1); $flag=0;} #grab new email from lines } } close(IN); #close $file } sub passwd{ #change to url escape codes in password #URL ESCAPE CODES $_=$pass; s/\%/\%25/g; s/\#/\%23/g; s/\$/\%24/g; s/\&/\%26/g; s/\//\%2F/g; s/\:/\%3A/g; s/\;/\%3B/g; s/\/\%3E/g; s/\?/\%3F/g; s/\@/\%40/g; s/\[/\%5B/g; s/\\/\%5C/g; s/\]/\%5D/g; s/\^/\%5E/g; s/\`/\%60/g; s/\{/\%7B/g; s/\|/\%7C/g; s/\}/\%7D/g; s/\~/\%7E/g; $pass=$_; } sub msg{ #THE HTML CODED CHARACTER SET [ISO-8859-1] chomp; s/(.+)/$1/; #get just the subject #now replace any special characters s/\&\#33\;/!/g; #Exclamation mark s/\&\#34\;/"/g; s/\"\;/"/g; #Quotation mark s/\&\#35\;/#/g; #Number sign s/\&\#36\;/\$/g; #Dollar sign s/\&\#37\;/%/g; #Percent sign s/\&\#38\;/&/g; s/\&\;/&/g; #Ampersand s/\&\#39\;/'/g; #Apostrophe s/\&\#40\;/(/g; #Left parenthesis s/\&\#41\;/)/g; #Right parenthesis s/\&\#42\;/*/g; #Asterisk s/\&\#43\;/+/g; #Plus sign s/\&\#44\;/,/g; #Comma s/\&\#45\;/-/g; #Hyphen s/\&\#46\;/./g; #Period (fullstop) s/\&\#47\;/\//g; #Solidus (slash) s/\&\#58\;/:/g; #Colon s/\&\#59\;/\;/g; #Semi-colon s/\&\#60\;//g; s/\>\;//g; #Greater than s/\&\#63\;/\?/g; #Question mark s/\&\#64\;/\@/g; #Commercial at s/\&\#91\;/\[/g; #Left square bracket s/\&\#92\;/\\/g; #Reverse solidus (backslash) s/\&\#93\;/\]/g; #Right square bracket s/\&\#94\;/\^/g; #Caret s/\&\#95\;/_/g; #Horizontal bar (underscore) s/\&\#96\;/\`/g; #Acute accent s/\&\#123\;/\{/g; #Left curly brace s/\&\#124\;/|/g; #Vertical bar s/\&\#125\;/\}/g; #Right curly brace s/\&\#126\;/~/g; #Tilde s/\&\#161\;/¡/g; #Inverted exclamation s/\&\#162\;/¢/g; #Cent sign s/\&\#163\;/£/g; #Pound sterling s/\&\#164\;/¤/g; #General currency sign s/\&\#165\;/¥/g; #Yen sign s/\&\#166\;/¦/g; #Broken vertical bar s/\&\#167\;/§/g; #Section sign s/\&\#168\;/¨/g; #Umlaut (dieresis) s/\&\#169\;/©/g; s/\©\;/©/g; #Copyright s/\&\#170\;/ª/g; #Feminine ordinal s/\&\#171\;/«/g; #Left angle quote, guillemotleft s/\&\#172\;/¬/g; #Not sign s/\&\#174\;/®/g; #Registered trademark s/\&\#175\;/¯/g; #Macron accent s/\&\#176\;/°/g; #Degree sign s/\&\#177\;/±/g; #Plus or minus s/\&\#178\;/²/g; #Superscript two s/\&\#179\;/³/g; #Superscript three s/\&\#180\;/´/g; #Acute accent s/\&\#181\;/µ/g; #Micro sign s/\&\#182\;/¶/g; #Paragraph sign s/\&\#183\;/·/g; #Middle dot s/\&\#184\;/¸/g; #Cedilla s/\&\#185\;/¹/g; #Superscript one s/\&\#186\;/º/g; #Masculine ordinal s/\&\#187\;/»/g; #Right angle quote, guillemotright s/\&\#188\;/¼/g; s/\¼\;/¼/g; # Fraction one-fourth s/\&\#189\;/½/g; s/\½\;/½/g; # Fraction one-half s/\&\#190\;/¾/g; s/\¾\;/¾/g; # Fraction three-fourths s/\&\#191\;/¿/g; #Inverted question mark s/\&\#192\;/À/g; #Capital A, grave accent s/\&\#193\;/Á/g; #Capital A, acute accent s/\&\#194\;/Â/g; #Capital A, circumflex accent s/\&\#195\;/Ã/g; #Capital A, tilde s/\&\#196\;/Ä/g; #Capital A, dieresis or umlaut mark s/\&\#197\;/Å/g; #Capital A, ring s/\&\#198\;/Æ/g; #Capital AE dipthong (ligature) s/\&\#199\;/Ç/g; #Capital C, cedilla s/\&\#200\;/È/g; #Capital E, grave accent s/\&\#201\;/É/g; #Capital E, acute accent s/\&\#202\;/Ê/g; #Capital E, circumflex accent s/\&\#203\;/Ë/g; #Capital E, dieresis or umlaut mark s/\&\#204\;/Ì/g; #Capital I, grave accent s/\&\#205\;/Í/g; #Capital I, acute accent s/\&\#206\;/Î/g; #Capital I, circumflex accent s/\&\#207\;/Ï/g; #Capital I, dieresis or umlaut mark s/\&\#208\;/Ð/g; #Capital Eth, Icelandic s/\&\#209\;/Ñ/g; #Capital N, tilde s/\&\#210\;/Ò/g; #Capital O, grave accent s/\&\#211\;/Ó/g; #Capital O, acute accent s/\&\#212\;/Ô/g; #Capital O, circumflex accent s/\&\#213\;/Õ/g; #Capital O, tilde s/\&\#214\;/Ö/g; #Capital O, dieresis or umlaut mark s/\&\#215\;/×/g; #Multiply sign s/\&\#216\;/Ø/g; #Capital O, slash s/\&\#217\;/Ù/g; #Capital U, grave accent s/\&\#218\;/Ú/g; #Capital U, acute accent s/\&\#219\;/Û/g; #Capital U, circumflex accent s/\&\#220\;/Ü/g; #Capital U, dieresis or umlaut mark s/\&\#221\;/Ý/g; #Capital Y, acute accent s/\&\#222\;/Þ/g; #Capital THORN, Icelandic s/\&\#223\;/ß/g; #Small sharp s, German (sz ligature) s/\&\#224\;/à/g; #Small a, grave accent s/\&\#225\;/á/g; #Small a, acute accent s/\&\#226\;/â/g; #Small a, circumflex accent s/\&\#227\;/ã/g; #Small a, tilde s/\&\#228\;/ä/g; #Small a, dieresis or umlaut mark s/\&\#229\;/å/g; #Small a, ring s/\&\#230\;/æ/g; #Small ae dipthong (ligature) s/\&\#231\;/ç/g; #Small c, cedilla s/\&\#232\;/è/g; #Small e, grave accent s/\&\#233\;/é/g; #Small e, acute accent s/\&\#234\;/ê/g; #Small e, circumflex accent s/\&\#235\;/ë/g; #Small e, dieresis or umlaut mark s/\&\#236\;/ì/g; #Small i, grave accent s/\&\#237\;/í/g; #Small i, acute accent s/\&\#238\;/î/g; #Small i, circumflex accent s/\&\#239\;/ï/g; #Small i, dieresis or umlaut mark s/\&\#240\;/ð/g; #Small eth, Icelandic s/\&\#241\;/ñ/g; #Small n, tilde s/\&\#242\;/ò/g; #Small o, grave accent s/\&\#243\;/ó/g; #Small o, acute accent s/\&\#244\;/ô/g; #Small o, circumflex accent s/\&\#245\;/õ/g; #Small o, tilde s/\&\#246\;/ö/g; #Small o, dieresis or umlaut mark s/\&\#247\;/÷/g; #Division sign s/\&\#248\;/ø/g; #Small o, slash s/\&\#249\;/ù/g; #Small u, grave accent s/\&\#250\;/ú/g; #Small u, acute accent s/\&\#251\;/û/g; #Small u, circumflex accent s/\&\#252\;/ü/g; #Small u, dieresis or umlaut mark s/\&\#253\;/ý/g; #Small y, acute accent s/\&\#254\;/þ/g; #Small thorn, Icelandic s/\&\#255\;/ÿ/g; #Small y, dieresis or umlaut mark s/^\s+//; return $_; }

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  • CodePlex Daily Summary for Tuesday, January 25, 2011

    CodePlex Daily Summary for Tuesday, January 25, 2011Popular ReleasesKooboo CMS: Kooboo CMS 3.0 CTP: Files in this downloadkooboo_CMS.zip: The kooboo application files Content_DBProvider.zip: Additional content database implementation of MSSQL, RavenDB and SQLCE. Default is XML based database. To use them, copy the related dlls into web root bin folder and remove old content provider dlls. Content provider has the name like "Kooboo.CMS.Content.Persistence.SQLServer.dll" View_Engines.zip: Supports of Razor, webform and NVelocity view engine. Copy the dlls into web root bin folder to enable...UOB & ME: UOB ME 2.6: UOB ME 2.6????: ???? V1.0: ???? V1.0 ??Developer Guidance - Onboarding Windows Phone 7: Fuel Tracker Source: Release NotesThis project is almost complete. We'll be making small updates to the code and documentation over the next week or so. We look forward to your feedback. This documentation and accompanying sample application will get you started creating a complete application for Windows Phone 7. You will learn about common developer issues in the context of a simple fuel-tracking application named Fuel Tracker. Some of the tasks that you will learn include the following: Creating a UI that...Password Generator: 2.2: Parallel password generation Password strength calculation ( Same method used by Microsoft here : https://www.microsoft.com/protect/fraud/passwords/checker.aspx ) Minor code refactoringASP.NET MVC Project Awesome, jQuery Ajax helpers (controls): 1.6.2: A rich set of helpers (controls) that you can use to build highly responsive and interactive Ajax-enabled Web applications. These helpers include Autocomplete, AjaxDropdown, Lookup, Confirm Dialog, Popup Form, Popup and Pager the html generation has been optimized, the html page size is much smaller nowFacebook Graph Toolkit: Facebook Graph Toolkit 0.6: new Facebook Graph objects: Application, Page, Post, Comment Improved Intellisense documentation new Graph Api connections: albums, photos, posts, feed, home, friends JSON Toolkit upgraded to version 0.9 (beta release) with bug fixes and new features bug fixed: error when handling empty JSON arrays bug fixed: error when handling JSON array with square or large brackets in the message bug fixed: error when handling JSON obejcts with double quotation in the message bug fixed: erro...Microsoft All-In-One Code Framework: Visual Studio 2008 Code Samples 2011-01-23: Code samples for Visual Studio 2008BloodSim: BloodSim - 1.4.0.0: This version requires an update for WControls.dll. - Removed option to use Old Rune Strike - Fixed an issue that was causing Ratings to not properly update when running Progressive simulations - Ability data is now loaded from an XML file in the BloodSim directory that is user editable. This data will be reloaded each time a fresh simulation is run. - Added toggle for showing Graph window. When unchecked, output data will instead be saved to a text file in the BloodSim directory based on the...MVVM Light Toolkit: MVVM Light Toolkit V3 SP1 (3): Instructions for installation: http://www.galasoft.ch/mvvm/installing/manually/ Includes the hotfix templates for Windows Phone 7 development. This is only relevant if you didn't already install the hotfix described at http://blog.galasoft.ch/archive/2010/07/22/mvvm-light-hotfix-for-windows-phone-7-developer-tools-beta.aspx.Community Forums NNTP bridge: Community Forums NNTP Bridge V42: Release of the Community Forums NNTP Bridge to access the social and anwsers MS forums with a single, open source NNTP bridge. This release has added some features / bugfixes: Bugfix: Decoding of Subject now also supports multi-line subjects (occurs only if you have very long subjects with non-ASCII characters)Minecraft Tools: Minecraft Topographical Survey 1.3: MTS requires version 4 of the .NET Framework - you must download it from Microsoft if you have not previously installed it. This version of MTS adds automatic block list updates, so MTS will recognize blocks added in game updates properly rather than drawing them in bright pink. New in this version of MTS: Support for all new blocks added since the Halloween update Auto-update of blockcolors.xml to support future game updates A splash screen that shows while the program searches for upd...StyleCop for ReSharper: StyleCop for ReSharper 5.1.14996.000: New Features: ============= This release is just compiled against the latest release of JetBrains ReSharper 5.1.1766.4 Previous release: A considerable amount of work has gone into this release: Huge focus on performance around the violation scanning subsystem: - caching added to reduce IO operations around reading and merging of settings files - caching added to reduce creation of expensive objects Users should notice condsiderable perf boost and a decrease in memory usage. Bug Fixes...jQuery ASP.Net MVC Controls: Version 1.2.0.0: jqGrid 3.8 support jquery 1.4 support New and exciting features Many bugfixes Complete separation from the jquery, & jqgrid codeMediaScout: MediaScout 3.0 Preview 4: Update ReleaseCoding4Fun Tools: Coding4Fun.Phone.Toolkit v1: Coding4Fun.Phone.Toolkit v1MFCMAPI: January 2011 Release: Build: 6.0.0.1024 Full release notes at SGriffin's blog. If you just want to run the tool, get the executable. If you want to debug it, get the symbol file and the source. The 64 bit build will only work on a machine with Outlook 2010 64 bit installed. All other machines should use the 32 bit build, regardless of the operating system. Facebook BadgeAutoLoL: AutoLoL v1.5.4: Added champion: Renekton Removed automatic file association Fix: The recent files combobox didn't always open a file when an item was selected Fix: Removing a recently opened file caused an errorDotNetNuke® Community Edition: 05.06.01: Major Highlights Fixed issue to remove preCondition checks when upgrading to .Net 4.0 Fixed issue where some valid domains were failing email validation checks. Fixed issue where editing Host menu page settings assigns the page to a Portal. Fixed issue which caused XHTML validation problems in 5.6.0 Fixed issue where an aspx page in any subfolder was inaccessible. Fixed issue where Config.Touch method signature had an unintentional breaking change in 5.6.0 Fixed issue which caused...iTracker Asp.Net Starter Kit: Version 3.0.0: This is the inital release of the version 3.0.0 Visual Studio 2010 (.Net 4.0) remake of the ITracker application. I connsider this a working, stable application but since there are still some features missing to make it "complete" I'm leaving it listed as a "beta" release. I am hoping to make it feature complete for v3.1.0 but anything is possible.New Projectsarchicop: Make your .NET Code Clean with ArchiCop! ArchiCop is a Visual Studio tool to manage complex .NET code and achieve high Code Quality. It's very simple to use. With ArchiCop you can validate references, project properties and group your projects in layers.Blitzkrieg Board Game (1965): I'm currently working on making Blitzkrieg using .NET 4 and WPF (http://www.boardgamegeek.com/boardgame/4168/blitzkrieg). The goal of this project is to make the game extremely mod-able, by allowing the end-user to change the sprites, game object types, map cell types, and more.Candy: Candy is modern gene-fishing platform which enables Biologists to find candidate genes with ease. Candy is implemented in C# and uses Silverlight to deliver a rich user experience.CMScreator: Content Management System CreatorDecoratorSharp: DecoratorSharp is a Decorator from python.Dorm (beta) - .Net ORM: It’s a light-weight ORM framework for .Net. The idea is to provide all the productivity of an ORM tool without abstracting entirely the database, therefore giving the developer a finer degree of control on data manipulation.DxStudyPro: DirectX Study ProFRCRobotCode: Lightsabers FRC robot code.grouptalk: grouptalkHeejooShop: Heejoo ShopIC Colorful: The aim of this project is to implement an algorithm allowing color-blind people to distinguish colors that they fail to distinguish in regular circumstances. This project is implemented as a DirectShow filter, thus could be used as a video codec as well as live video stream traItzben: Universally useful XAML behaviors, styles, and value converters. Developed in C# for WPF, Silverlight, and WP7.JSON Toolkit: JSON Toolkit is a .NET library written in C# used to handle JSON objects, convert string to JSON objects and obtainn values from them.Materials Data Centre: This project is to create aa materials data centre; a repository for experimental data. See www.materialsdatacentre.com It is built on Microsoft SharePoint with functionality exposed through Web Services.OpenCLI: OpenCLI brings a linux style CLI written in .NET. It acts as a portal from linux style commands, to their commands on the windows system. It is useful to Sysadmins, who wish to deny their uses to the power of Command Prompt, yet want them to be able to user a CLI.Pinguim Cook .Net - Automação de Restaurantes: Em CriaçãoPixination: Pixination is a tiny color picker to get any color from the screen. You will have a collection of color patterns to work with. Developed on C# with Framework 2.0Project Acolythe: Project Acolythe is the codename for a new Open Source RPG. Based upon different ideas from currently available RPGs the Game will have an incredible depth in gameplay. The Team behind is currently a bit small, so if you are interessted to help us out, leave a note ;)Propono: Blogging application based on ASP.NET MVCSharePoint 2010 Excel Export Feature: This feature can be used to export SharePoint lists to Excel Files (.xslx). You can upload templates for the excel export.SilverlightMedia JavaScript Library: A JavaScript library making it quick and easy to work with any web-based media player built with Silverlight. You can take control of any Silverlight media player using pure JavaScript. This facilitates useful scenarios e.g. creating HTML controls, displaying player status, etc.Soluciones: El project contiene herramientas de marketing para todo tipo de tama~o de empresas. Estaba basada en el standard definido por el mercado mismo. Estare publicando las descripcion del project en mas detalle.Soluciones Integrales: El projecto ve la necesidad de poder dar soporte al area de Marketing La finalidad de este proyecto es la implementacion de herramientas de marketing para que las empresas puedan ser mas eficientes al momento de procesar tareas de marketing. Les permitira: - enviar correos masivos - actualizacion de websites a distancia - ingreso de nuevos clientes a dasedatosSparkle Engine: Sparkle engine is a library for various types of effects. Currently I'm working on creating some basic text effects. Storyline Toolbox: Storyline Toolbox 2 is a web platform helping visualize the Storyline method. Version 1 of the Storyline Toolbox was developed in Perl by Linpro (now Redpill) in 2003. This project aims to providy a better user experience for students and teachers using the Storyline Toolbox.TFS Workbench Plugins: This project is dedicated to extending the functionality of the greatest Scrum tool, TFS Workbench.Tireguit Nmon Analyzer: An AIX and linux Nmon Analyzer; It uses SQL Compact 3.5 and C#. For more information on Nmon please visit http://nmon.sourceforge.net/pmwiki.php.uglifycs: Uglify.JS (https://github.com/mishoo/UglifyJS) and jsBeautifier (http://jsbeautifier.org) wrapped using JavaScript.NET (http://javascriptnet.codeplex.com) for use in .NET projects.usea: my study projectWindows Phone Cryptographic Storage: A C# library for easily storing and protecting data with a password on Windows Phone. The data is encrypted and authenticated with keys derived from a user provided password. Yahoo! Decoder: Yahoo! Decoder helps you read Yahoo! messenger chat archives offline with full support of smilies and links.????: “????”?????????????????????WinForm????,??C#????。?????????,????(2??),????!

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  • Down Tools Week Cometh: Kissing Goodbye to CVs/Resumes and Cover Letters

    - by Bart Read
    I haven't blogged about what I'm doing in my (not so new) temporary role as Red Gate's technical recruiter, mostly because it's been routine, business as usual stuff, and because I've been trying to understand the role by doing it. I think now though the time has come to get a little more radical, so I'm going to tell you why I want to largely eliminate CVs/resumes and cover letters from the application process for some of our technical roles, and why I think that might be a good thing for candidates (and for us). I have a terrible confession to make, or at least it's a terrible confession for a recruiter: I don't really like CV sifting, or reading cover letters, and, unless I've misread the mood around here, neither does anybody else. It's dull, it's time-consuming, and it's somewhat soul destroying because, when all is said and done, you're being paid to be incredibly judgemental about people based on relatively little information. I feel like I've dirtied myself by saying that - I mean, after all, it's a core part of my job - but it sucks, it really does. (And, of course, the truth is I'm still a software engineer at heart, and I'm always looking for ways to do things better.) On the flip side, I've never met anyone who likes writing their CV. It takes hours and hours of faffing around and massaging it into shape, and the whole process is beset by a gnawing anxiety, frustration, and insecurity. All you really want is a chance to demonstrate your skills - not just talk about them - and how do you do that in a CV or cover letter? Often the best candidates will include samples of their work (a portfolio, screenshots, links to websites, product downloads, etc.), but sometimes this isn't possible, or may not be appropriate, or you just don't think you're allowed because of what your school/university careers service has told you (more commonly an issue with grads, obviously). And what are we actually trying to find out about people with all of this? I think the common criteria are actually pretty basic: Smart Gets things done (thanks for these two Joel) Not an a55hole* (sorry, have to get around Simple Talk's swear filter - and thanks to Professor Robert I. Sutton for this one) *Of course, everyone has off days, and I don't honestly think we're too worried about somebody being a bit grumpy every now and again. We can do a bit better than this in the context of the roles I'm talking about: we can be more specific about what "gets things done" means, at least in part. For software engineers and interns, the non-exhaustive meaning of "gets things done" is: Excellent coder For test engineers, the non-exhaustive meaning of "gets things done" is: Good at finding problems in software Competent coder Team player, etc., to me, are covered by "not an a55hole". I don't expect people to be the life and soul of the party, or a wild extrovert - that's not what team player means, and it's not what "not an a55hole" means. Some of our best technical staff are quiet, introverted types, but they're still pleasant to work with. My problem is that I don't think the initial sift really helps us find out whether people are smart and get things done with any great efficacy. It's better than nothing, for sure, but it's not as good as it could be. It's also contentious, and potentially unfair/inequitable - if you want to get an idea of what I mean by this, check out the background information section at the bottom. Before I go any further, let's look at the Red Gate recruitment process for technical staff* as it stands now: (LOTS of) People apply for jobs. All these applications go through a brutal process of manual sifting, which eliminates between 75 and 90% of them, depending upon the role, and the time of year**. Depending upon the role, those who pass the sift will be sent an assessment or telescreened. For the purposes of this blog post I'm only interested in those that are sent some sort of programming assessment, or bug hunt. This means software engineers, test engineers, and software interns, which are the roles for which I receive the most applications. The telescreen tends to be reserved for project or product managers. Those that pass the assessment are invited in for first interview. This interview is mostly about assessing their technical skills***, although we're obviously on the look out for cultural fit red flags as well. If the first interview goes well we'll invite candidates back for a second interview. This is where team/cultural fit is really scoped out. We also use this interview to dive more deeply into certain areas of their skillset, and explore any concerns that may have come out of the first interview (these obviously won't have been serious or obvious enough to cause a rejection at that point, but are things we do need to look into before we'd consider making an offer). We might subsequently invite them in for lunch before we make them an offer. This tends to happen when we're recruiting somebody for a specific team and we'd like them to meet all the people they'll be working with directly. It's not an interview per se, but can prove pivotal if they don't gel with the team. Anyone who's made it this far will receive an offer from us. *We have a slightly quirky definition of "technical staff" as it relates to the technical recruiter role here. It includes software engineers, test engineers, software interns, user experience specialists, technical authors, project managers, product managers, and development managers, but does not include product support or information systems roles. **For example, the quality of graduate applicants overall noticeably drops as the academic year wears on, which is not to say that by now there aren't still stars in there, just that they're fewer and further between. ***Some organisations prefer to assess for team fit first, but I think assessing technical skills is a more effective initial filter - if they're the nicest person in the world, but can't cut a line of code they're not going to work out. Now, as I suggested in the title, Red Gate's Down Tools Week is upon us once again - next week in fact - and I had proposed as a project that we refactor and automate the first stage of marking our programming assessments. Marking assessments, and in fact organising the marking of them, is a somewhat time-consuming process, and we receive many assessment solutions that just don't make the cut, for whatever reason. Whilst I don't think it's possible to fully automate marking, I do think it ought to be possible to run a suite of automated tests over each candidate's solution to see whether or not it behaves correctly and, if it does, move on to a manual stage where we examine the code for structure, decomposition, style, readability, maintainability, etc. Obviously it's possible to use tools to generate potentially helpful metrics for some of these indices as well. This would obviously reduce the marking workload, and would provide candidates with quicker feedback about whether they've been successful - though I do wonder if waiting a tactful interval before sending a (nicely written) rejection might be wise. I duly scrawled out a picture of my ideal process, which looked like this: The problem is, as soon as I'd roughed it out, I realised that fundamentally it wasn't an ideal process at all, which explained the gnawing feeling of cognitive dissonance I'd been wrestling with all week, whilst I'd been trying to find time to do this. Here's what I mean. Automated assessment marking, and the associated infrastructure around that, makes it much easier for us to deal with large numbers of assessments. This means we can be much more permissive about who we send assessments out to or, in other words, we can give more candidates the opportunity to really demonstrate their skills to us. And this leads to a question: why not give everyone the opportunity to demonstrate their skills, to show that they're smart and can get things done? (Two or three of us even discussed this in the down tools week hustings earlier this week.) And isn't this a lot simpler than the alternative we'd been considering? (FYI, this was automated CV/cover letter sifting by some form of textual analysis to ideally eliminate the worst 50% or so of applications based on an analysis of the 20,000 or so historical applications we've received since 2007 - definitely not the basic keyword analysis beloved of recruitment agencies, since this would eliminate hardly anyone who was awful, but definitely would eliminate stellar Oxbridge candidates - #fail - or some nightmarishly complex Google-like system where we profile all our currently employees, only to realise that we're never going to get representative results because we don't have a statistically significant sample size in any given role - also #fail.) No, I think the new way is better. We let people self-select. We make them the masters (or mistresses) of their own destiny. We give applicants the power - we put their fate in their hands - by giving them the chance to demonstrate their skills, which is what they really want anyway, instead of requiring that they spend hours and hours creating a CV and cover letter that I'm going to evaluate for suitability, and make a value judgement about, in approximately 1 minute (give or take). It doesn't matter what university you attended, it doesn't matter if you had a bad year when you took your A-levels - here's your chance to shine, so take it and run with it. (As a side benefit, we cut the number of applications we have to sift by something like two thirds.) WIN! OK, yeah, sounds good, but will it actually work? That's an excellent question. My gut feeling is yes, and I'll justify why below (and hopefully have gone some way towards doing that above as well), but what I'm proposing here is really that we run an experiment for a period of time - probably a couple of months or so - and measure the outcomes we see: How many people apply? (Wouldn't be surprised or alarmed to see this cut by a factor of ten.) How many of them submit a good assessment? (More/less than at present?) How much overhead is there for us in dealing with these assessments compared to now? What are the success and failure rates at each interview stage compared to now? How many people are we hiring at the end of it compared to now? I think it'll work because I hypothesize that, amongst other things: It self-selects for people who really want to work at Red Gate which, at the moment, is something I have to try and assess based on their CV and cover letter - but if you're not that bothered about working here, why would you complete the assessment? Candidates who would submit a shoddy application probably won't feel motivated to do the assessment. Candidates who would demonstrate good attention to detail in their CV/cover letter will demonstrate good attention to detail in the assessment. In general, only the better candidates will complete and submit the assessment. Marking assessments is much less work so we'll be able to deal with any increase that we see (hopefully we will see). There are obviously other questions as well: Is plagiarism going to be a problem? Is there any way we can detect/discourage potential plagiarism? How do we assess candidates' education and experience? What about their ability to communicate in writing? Do we still want them to submit a CV afterwards if they pass assessment? Do we want to offer them the opportunity to tell us a bit about why they'd like the job when they submit their assessment? How does this affect our relationship with recruitment agencies we might use to hire for these roles? So, what's the objective for next week's Down Tools Week? Pretty simple really - we want to implement this process for the Graduate Software Engineer and Software Engineer positions that you can find on our website. I will be joined by a crack team of our best developers (Kevin Boyle, and new Red-Gater, Sam Blackburn), and recruiting hostess with the mostest Laura McQuillen, and hopefully a couple of others as well - if I can successfully twist more arms before Monday.* Hopefully by next Friday our experiment will be up and running, and we may have changed the way Red Gate recruits software engineers for good! Stay tuned and we'll let you know how it goes! *I'm going to play dirty by offering them beer and chocolate during meetings. Some background information: how agonising over the initial CV/cover letter sift helped lead us to bin it off entirely The other day I was agonising about the new university/good degree grade versus poor A-level results issue, and decided to canvas for other opinions to see if there was something I could do that was fairer than my current approach, which is almost always to reject. This generated quite an involved discussion on our Yammer site: I'm sure you can glean a pretty good impression of my own educational prejudices from that discussion as well, although I'm very open to changing my opinion - hopefully you've already figured that out from reading the rest of this post. Hopefully you can also trace a logical path from agonising about sifting to, "Uh, hang on, why on earth are we doing this anyway?!?" Technorati Tags: recruitment,hr,developers,testers,red gate,cv,resume,cover letter,assessment,sea change

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  • Selling Federal Enterprise Architecture (EA)

    - by TedMcLaughlan
    Selling Federal Enterprise Architecture A taxonomy of subject areas, from which to develop a prioritized marketing and communications plan to evangelize EA activities within and among US Federal Government organizations and constituents. Any and all feedback is appreciated, particularly in developing and extending this discussion as a tool for use – more information and details are also available. "Selling" the discipline of Enterprise Architecture (EA) in the Federal Government (particularly in non-DoD agencies) is difficult, notwithstanding the general availability and use of the Federal Enterprise Architecture Framework (FEAF) for some time now, and the relatively mature use of the reference models in the OMB Capital Planning and Investment (CPIC) cycles. EA in the Federal Government also tends to be a very esoteric and hard to decipher conversation – early apologies to those who agree to continue reading this somewhat lengthy article. Alignment to the FEAF and OMB compliance mandates is long underway across the Federal Departments and Agencies (and visible via tools like PortfolioStat and ITDashboard.gov – but there is still a gap between the top-down compliance directives and enablement programs, and the bottom-up awareness and effective use of EA for either IT investment management or actual mission effectiveness. "EA isn't getting deep enough penetration into programs, components, sub-agencies, etc.", verified a panelist at the most recent EA Government Conference in DC. Newer guidance from OMB may be especially difficult to handle, where bottom-up input can't be accurately aligned, analyzed and reported via standardized EA discipline at the Agency level – for example in addressing the new (for FY13) Exhibit 53D "Agency IT Reductions and Reinvestments" and the information required for "Cloud Computing Alternatives Evaluation" (supporting the new Exhibit 53C, "Agency Cloud Computing Portfolio"). Therefore, EA must be "sold" directly to the communities that matter, from a coordinated, proactive messaging perspective that takes BOTH the Program-level value drivers AND the broader Agency mission and IT maturity context into consideration. Selling EA means persuading others to take additional time and possibly assign additional resources, for a mix of direct and indirect benefits – many of which aren't likely to be realized in the short-term. This means there's probably little current, allocated budget to work with; ergo the challenge of trying to sell an "unfunded mandate". Also, the concept of "Enterprise" in large Departments like Homeland Security tends to cross all kinds of organizational boundaries – as Richard Spires recently indicated by commenting that "...organizational boundaries still trump functional similarities. Most people understand what we're trying to do internally, and at a high level they get it. The problem, of course, is when you get down to them and their system and the fact that you're going to be touching them...there's always that fear factor," Spires said. It is quite clear to the Federal IT Investment community that for EA to meet its objective, understandable, relevant value must be measured and reported using a repeatable method – as described by GAO's recent report "Enterprise Architecture Value Needs To Be Measured and Reported". What's not clear is the method or guidance to sell this value. In fact, the current GAO "Framework for Assessing and Improving Enterprise Architecture Management (Version 2.0)", a.k.a. the "EAMMF", does not include words like "sell", "persuade", "market", etc., except in reference ("within Core Element 19: Organization business owner and CXO representatives are actively engaged in architecture development") to a brief section in the CIO Council's 2001 "Practical Guide to Federal Enterprise Architecture", entitled "3.3.1. Develop an EA Marketing Strategy and Communications Plan." Furthermore, Core Element 19 of the EAMMF is advised to be applied in "Stage 3: Developing Initial EA Versions". This kind of EA sales campaign truly should start much earlier in the maturity progress, i.e. in Stages 0 or 1. So, what are the understandable, relevant benefits (or value) to sell, that can find an agreeable, participatory audience, and can pave the way towards success of a longer-term, funded set of EA mechanisms that can be methodically measured and reported? Pragmatic benefits from a useful EA that can help overcome the fear of change? And how should they be sold? Following is a brief taxonomy (it's a taxonomy, to help organize SME support) of benefit-related subjects that might make the most sense, in creating the messages and organizing an initial "engagement plan" for evangelizing EA "from within". An EA "Sales Taxonomy" of sorts. We're not boiling the ocean here; the subjects that are included are ones that currently appear to be urgently relevant to the current Federal IT Investment landscape. Note that successful dialogue in these topics is directly usable as input or guidance for actually developing early-stage, "Fit-for-Purpose" (a DoDAF term) Enterprise Architecture artifacts, as prescribed by common methods found in most EA methodologies, including FEAF, TOGAF, DoDAF and our own Oracle Enterprise Architecture Framework (OEAF). The taxonomy below is organized by (1) Target Community, (2) Benefit or Value, and (3) EA Program Facet - as in: "Let's talk to (1: Community Member) about how and why (3: EA Facet) the EA program can help with (2: Benefit/Value)". Once the initial discussion targets and subjects are approved (that can be measured and reported), a "marketing and communications plan" can be created. A working example follows the Taxonomy. Enterprise Architecture Sales Taxonomy Draft, Summary Version 1. Community 1.1. Budgeted Programs or Portfolios Communities of Purpose (CoPR) 1.1.1. Program/System Owners (Senior Execs) Creating or Executing Acquisition Plans 1.1.2. Program/System Owners Facing Strategic Change 1.1.2.1. Mandated 1.1.2.2. Expected/Anticipated 1.1.3. Program Managers - Creating Employee Performance Plans 1.1.4. CO/COTRs – Creating Contractor Performance Plans, or evaluating Value Engineering Change Proposals (VECP) 1.2. Governance & Communications Communities of Practice (CoP) 1.2.1. Policy Owners 1.2.1.1. OCFO 1.2.1.1.1. Budget/Procurement Office 1.2.1.1.2. Strategic Planning 1.2.1.2. OCIO 1.2.1.2.1. IT Management 1.2.1.2.2. IT Operations 1.2.1.2.3. Information Assurance (Cyber Security) 1.2.1.2.4. IT Innovation 1.2.1.3. Information-Sharing/ Process Collaboration (i.e. policies and procedures regarding Partners, Agreements) 1.2.2. Governing IT Council/SME Peers (i.e. an "Architects Council") 1.2.2.1. Enterprise Architects (assumes others exist; also assumes EA participants aren't buried solely within the CIO shop) 1.2.2.2. Domain, Enclave, Segment Architects – i.e. the right affinity group for a "shared services" EA structure (per the EAMMF), which may be classified as Federated, Segmented, Service-Oriented, or Extended 1.2.2.3. External Oversight/Constraints 1.2.2.3.1. GAO/OIG & Legal 1.2.2.3.2. Industry Standards 1.2.2.3.3. Official public notification, response 1.2.3. Mission Constituents Participant & Analyst Community of Interest (CoI) 1.2.3.1. Mission Operators/Users 1.2.3.2. Public Constituents 1.2.3.3. Industry Advisory Groups, Stakeholders 1.2.3.4. Media 2. Benefit/Value (Note the actual benefits may not be discretely attributable to EA alone; EA is a very collaborative, cross-cutting discipline.) 2.1. Program Costs – EA enables sound decisions regarding... 2.1.1. Cost Avoidance – a TCO theme 2.1.2. Sequencing – alignment of capability delivery 2.1.3. Budget Instability – a Federal reality 2.2. Investment Capital – EA illuminates new investment resources via... 2.2.1. Value Engineering – contractor-driven cost savings on existing budgets, direct or collateral 2.2.2. Reuse – reuse of investments between programs can result in savings, chargeback models; avoiding duplication 2.2.3. License Refactoring – IT license & support models may not reflect actual or intended usage 2.3. Contextual Knowledge – EA enables informed decisions by revealing... 2.3.1. Common Operating Picture (COP) – i.e. cross-program impacts and synergy, relative to context 2.3.2. Expertise & Skill – who truly should be involved in architectural decisions, both business and IT 2.3.3. Influence – the impact of politics and relationships can be examined 2.3.4. Disruptive Technologies – new technologies may reduce costs or mitigate risk in unanticipated ways 2.3.5. What-If Scenarios – can become much more refined, current, verifiable; basis for Target Architectures 2.4. Mission Performance – EA enables beneficial decision results regarding... 2.4.1. IT Performance and Optimization – towards 100% effective, available resource utilization 2.4.2. IT Stability – towards 100%, real-time uptime 2.4.3. Agility – responding to rapid changes in mission 2.4.4. Outcomes –measures of mission success, KPIs – vs. only "Outputs" 2.4.5. Constraints – appropriate response to constraints 2.4.6. Personnel Performance – better line-of-sight through performance plans to mission outcome 2.5. Mission Risk Mitigation – EA mitigates decision risks in terms of... 2.5.1. Compliance – all the right boxes are checked 2.5.2. Dependencies –cross-agency, segment, government 2.5.3. Transparency – risks, impact and resource utilization are illuminated quickly, comprehensively 2.5.4. Threats and Vulnerabilities – current, realistic awareness and profiles 2.5.5. Consequences – realization of risk can be mapped as a series of consequences, from earlier decisions or new decisions required for current issues 2.5.5.1. Unanticipated – illuminating signals of future or non-symmetric risk; helping to "future-proof" 2.5.5.2. Anticipated – discovering the level of impact that matters 3. EA Program Facet (What parts of the EA can and should be communicated, using business or mission terms?) 3.1. Architecture Models – the visual tools to be created and used 3.1.1. Operating Architecture – the Business Operating Model/Architecture elements of the EA truly drive all other elements, plus expose communication channels 3.1.2. Use Of – how can the EA models be used, and how are they populated, from a reasonable, pragmatic yet compliant perspective? What are the core/minimal models required? What's the relationship of these models, with existing system models? 3.1.3. Scope – what level of granularity within the models, and what level of abstraction across the models, is likely to be most effective and useful? 3.2. Traceability – the maturity, status, completeness of the tools 3.2.1. Status – what in fact is the degree of maturity across the integrated EA model and other relevant governance models, and who may already be benefiting from it? 3.2.2. Visibility – how does the EA visibly and effectively prove IT investment performance goals are being reached, with positive mission outcome? 3.3. Governance – what's the interaction, participation method; how are the tools used? 3.3.1. Contributions – how is the EA program informed, accept submissions, collect data? Who are the experts? 3.3.2. Review – how is the EA validated, against what criteria?  Taxonomy Usage Example:   1. To speak with: a. ...a particular set of System Owners Facing Strategic Change, via mandate (like the "Cloud First" mandate); about... b. ...how the EA program's visible and easily accessible Infrastructure Reference Model (i.e. "IRM" or "TRM"), if updated more completely with current system data, can... c. ...help shed light on ways to mitigate risks and avoid future costs associated with NOT leveraging potentially-available shared services across the enterprise... 2. ....the following Marketing & Communications (Sales) Plan can be constructed: a. Create an easy-to-read "Consequence Model" that illustrates how adoption of a cloud capability (like elastic operational storage) can enable rapid and durable compliance with the mandate – using EA traceability. Traceability might be from the IRM to the ARM (that identifies reusable services invoking the elastic storage), and then to the PRM with performance measures (such as % utilization of purchased storage allocation) included in the OMB Exhibits; and b. Schedule a meeting with the Program Owners, timed during their Acquisition Strategy meetings in response to the mandate, to use the "Consequence Model" for advising them to organize a rapid and relevant RFI solicitation for this cloud capability (regarding alternatives for sourcing elastic operational storage); and c. Schedule a series of short "Discovery" meetings with the system architecture leads (as agreed by the Program Owners), to further populate/validate the "As-Is" models and frame the "To Be" models (via scenarios), to better inform the RFI, obtain the best feedback from the vendor community, and provide potential value for and avoid impact to all other programs and systems. --end example -- Note that communications with the intended audience should take a page out of the standard "Search Engine Optimization" (SEO) playbook, using keywords and phrases relating to "value" and "outcome" vs. "compliance" and "output". Searches in email boxes, internal and external search engines for phrases like "cost avoidance strategies", "mission performance metrics" and "innovation funding" should yield messages and content from the EA team. This targeted, informed, practical sales approach should result in additional buy-in and participation, additional EA information contribution and model validation, development of more SMEs and quick "proof points" (with real-life testing) to bolster the case for EA. The proof point here is a successful, timely procurement that satisfies not only the external mandate and external oversight review, but also meets internal EA compliance/conformance goals and therefore is more transparently useful across the community. In short, if sold effectively, the EA will perform and be recognized. EA won’t therefore be used only for compliance, but also (according to a validated, stated purpose) to directly influence decisions and outcomes. The opinions, views and analysis expressed in this document are those of the author and do not necessarily reflect the views of Oracle.

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  • My computer freezes irregularly

    - by Manhim
    My computer started to freeze at irregular times for 3 weeks now. Please note that this question change with each things that i try. (For additional details) What happens My computer freezes, the video stops. (No graphic glitches, it just stops) Sound keeps playing up to some time (Usually 10-30 seconds) then stops playing. Sometimes, randomly, the screen on my G-15 keyboard flickers and I see caracters not at the right places. Usually happens for about 1-2 seconds and a bit before my computer freezes. I have to keep the power button pressed for 4 seconds to shut my computer down. I still hear my hard drives and fans working. Sometimes it works with no problems for a full day, some other times it just keeps freezing each time I restart my computer and I have to leave it for the rest of the day. Sometimes my mouse freezes for a fraction of a second (Like 0.01 to 0.2 seconds) quite randomly, usually before it freezes. No errors spotted by the "Action center" unlike when I had problems with my last video card on this system (Driver errors). My G-15 LCD screen also freezes. Sometimes my G-15 LCD screen flickers and caracters gets caried around temporary under heavy load. Now, most of the times, the BIOS hard disks boot order gets reversed for some reason and I have to put it to the right one and save each times I boot. (Might be unrelated, not sure, but it first started yesterday) Sometimes the BIOS doesn't detect my 750GB hard drive plugged in SATA1. What I did so far I have had similar problems in the past and I had changed my hard drive (It was faulty), so I tested my software RAID-0 array and it was faulty so I changed it. (I reinstalled Windows 7 with this part). I also tested with unplugging my secondary hard drive. My CPU was running at about 100 degree Celsius, I removed the dust between the fans and the heatsink and it's now between 45-55. I ran a CPU stress-test and it didn't freeze during the tests (using Prime95 on all cores) Ran a memory test (using memtest86+) for a single pass and there were no errors. Ran a GPU stress test with ati-tools and furmark and it didn't freeze during the tests. (No artefacts either) I had troubles with my graphic card when I got it, but I think that it got fixed with a driver update. I checked the voltages in my BIOS setup and they all seemed ok (±0.2 I think). I have ran on the computer without problems with Fedora 15 on an external hard drive (Appart that it couldn't load Gnome 3 and was reverting to Gnome 2, didn't want to install drivers since I use it on multiple computers) I used it to backup my files from the raid array to my 1TB hard drive for the reinstallation of Windows. (So the crashes only happenned on Windows) [The external hard drive is plugged directly on a SATA port] I contacted EVGA (My graphic card vendor) and pointed them on this question, I'm looking for an answer. Ran sensors on Fedora 15 and got this output: http://pastebin.com/0BHJnAvu Ran 6 short different CPU stress test on Fedora 15 (Haven't found any complete stress testers for Linux) and it didn't crash. Changed the thermal paste to some Artic Silver 5 for my CPU and stress tested the CPU, temperature was at 50 idle, then 64 highest and slowly went down to 62 during the test. Ran some stress testing with a temporary graphic card and it went ok. Ran furmark stress test with my original graphic card and it freezed again. GPU had a temp of 74C, a CPU temp of 58C and a mobo temp of 40C or 45C (Dunno which one it is from SpeedFan). Ran a furmark stress test and a CPU stress test at the same time, results: http://pastebin.com/2t6PLpdJ I have been using my computer without stressing it for about 2 hours now and no crashes yet. I also have disabled the AMD Cool'n'quiet function on the BIOS for a more regular power to the CPU. When I ran Furmark without C'n'q my computer didn't freeze but I had a "Driver Kernel Error" that have recovered (And Furmark crashed) all that while running a CPU stress test. The computer eventually frozed without me being at it, but this time my screen just went on sleep and I couldn't wake it. Using the stability tester in nTune my computer freezed again (In the same manner as before). I notived that Speedfan gives me a -12V of -16.97V and a -5V of -8.78V. I wonder if these numbers are reliable and if they are good or bad. I have swapped my G-15 with another basic USB keyboard (HP) and I have ran furmark for about 10 minutes with a CPU stability test running each 60 seconds for 30 seconds and my computer haven't crashed yet. Ran some more extended tests without my G-15 and it freezed like it usually do. Removed the nForce Hard disk controler. Disabled command queuing in the NVIDIA nForce SATA Controller for both port 0 and port 1 (Errors from the logs) Used CPUID HwMonitor, here are the voltages: http://pastebin.com/dfM7p4jV Changed some configurations in the motherboard BIOS: Disabled PEG Link Mode, Changed AI Tuning to Standard, Disabled the 1394 Controller, Disabled HD Audio, Disabled JMicron RAID controller and Disabled SATA Raid. When it happens When I play video games (Mostly) When I play flash games (Second most) When I'm looking at my desktop background (It rarely happens when I have a window open, but it does, sometimes) When my Graphic card and my CPU are stressed. Sometimes when my Graphic card is stressed. Never happenned while stressing only the CPU. Sometimes when my CPU is stressed. Specs Windows Seven x64 Home Premium Motherboard: M2N-SLI Deluxe CPU: AMD Phenom 9950 x2 @ 2.6GHz Memory: Kingston 4x2GB Dual Channel (Pretty basic memory sticks) Hard drives: Was 2x250GB (Western digital caviar) in raid-0 + 1TB (WD caviar black), I replaced the raid array with a 750GB (WD caviar black) [Yes I removed the array from the raid configurations] 750W Power supply No overcloking. Ever. There have been some power-downs like 4-5 weeks ago, but the problem didn't start immediately after. (I wasn't home, so my computer got shut-down) Event logs (Warnings, errors and critical errors) for the last 24 hours: http://pastebin.com/Bvvk31T7 My current to-try list Reinstall the drivers and software 1 by 1 and do extensive stress testing between each. Update the BIOS firmware to the most recent stable one. Change my motherboard. Status updates Keeping only the last 3 (28/06 04pm) More stress testing and still pass the tests. (28/06 03pm) Been stress testing for 10 minute straight now and 5 minutes with both CPU and GPU being stressed at the same time. (28/06 03pm) Stress-testing right now, so far no problems. A little hope Tests with Furmark and Prime95. Testing Windows bare-bone: 30 Minutes stress, no freeze. Installing an Anti-virus and some software, restarting computer. Testing with Anti-virus and some software (No drivers installed): 30 Minutes stress, no freeze. Installing audio drivers, restarting computer. Testing with the audio drivers: 30 Minutes stress, no freeze. Installing the latest graphic drivers from EVGA's website (without 3d vision since I don't use it), restarting computer. Testing with the graphic drivers: 30 Minutes stress, no freeze. Configuring Windows to my liking and installing more softwares. In this situation, how can I successfully pin-point the current hardware problem? (If it's a hardware problem) Because I don't really have the budget to just forget and replace everything. I also don't really have hardware to test-replace current hardware.

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  • Starting to make progress Was [MediaRecorder prepare() causes segfault]

    - by dwilde1
    Folks, I have a situation where my MediaRecorder instance causes a segfault. I'm working with a HTC Hero, Android 1.5+APIs. I've tried all variations, including 3gpp and H.263 and reducing the video resolution to 320x240. What am I missing? The state machine causes 4 MediaPlayer beeps and then turns on the video camera. Here's the pertinent source: UPDATE: ADDING SURFACE CREATE INFO I have rebooted the device based on previous answer to similar question. UPDATE 2: I seem to be following the MediaRecorder state machine perfectly, and if I trap out the MR code, the blank surface displays perfectly and everything else functions perfectly. I can record videos manually and play back via MediaPlayer in my code, so there should be nothing wrong with the underlying code. I've copied sample code on the surface and surfaceHolder code. I've looked at the MR instance in the Debug perspective in Eclipse and see that all (known) variables seem to be instantiated correctly. The setter calls are all now implemented in the exaxct order specced in the state diagram. UPDATE 3: I've tried all permission combinations: CAMERA + RECORD_AUDIO+RECORD_VIDEO, CAMERA only, RECORD_AUDIO+RECORD_VIDEO This is driving me bats! :))) UPDATE 4: starting to work... but with puzzling results. Based on info in bug #5050, I spaced everything out. I have now gotten the recorder to actually save a snippet of video (a whole 2160 bytes!), and I did it by spacing the view visibility, prepare() and start() w.a.a.a.a.a.y out (like several hundred milliseconds for each step). I think what happens is that either bringing the surface VISIBLE has delayed processing or else the start() steps on the prepare() operation before it is complete. What is now happening, however, is that my simple timer tickdown counter is getting clobbered. Is it now that the preview and save operations are causing my main process thread to become unavailable? I'm recording only 10fps at 176x144. Referencing the above code, I've added a timer tickdown after setPreviewDisplay(), prepare() and start(). As I say, it now functions to some degree, but the results still have anomalies. // in activity class definition protected MediaPlayer mPlayer; protected MediaRecorder mRecorder; protected boolean inCapture = false; protected int phaseCapture = 0; protected int durCapturePhase = INF; protected SurfaceView surface; protected SurfaceHolder surfaceHolder; // in onCreate() // panelPreview is an empty LinearLayout surface = new SurfaceView(getApplicationContext()); surfaceHolder = surface.getHolder(); surfaceHolder.setType(SurfaceHolder.SURFACE_TYPE_PUSH_BUFFERS); panelPreview.addView(surface); // in timer handler runnable if (mRecorder == null) mRecorder = new MediaRecorder(); mRecorder.setAudioSource(MediaRecorder.AudioSource.MIC); mRecorder.setVideoSource(MediaRecorder.VideoSource.CAMERA); mRecorder.setOutputFormat(MediaRecorder.OutputFormat.THREE_GPP); mRecorder.setAudioEncoder(MediaRecorder.AudioEncoder.AMR_NB); mRecorder.setOutputFile(path + "/" + vlip); mRecorder.setVideoSize(320, 240); mRecorder.setVideoFrameRate(15); mRecorder.setPreviewDisplay(surfaceHolder.getSurface()); panelPreview.setVisibility(LinearLayout.VISIBLE); mRecorder.prepare(); mRecorder.start(); Here is a complete log trace for the process run and crash: I/ActivityManager( 80): Start proc com.ejf.convince.jenplus for activity com.ejf.convince.jenplus/.JenPLUS: pid=17738 uid=10075 gids={1006, 3003} I/jdwp (17738): received file descriptor 10 from ADB W/System.err(17738): Can't dispatch DDM chunk 46454154: no handler defined W/System.err(17738): Can't dispatch DDM chunk 4d505251: no handler defined I/WindowManager( 80): Screen status=true, current orientation=-1, SensorEnabled=false I/WindowManager( 80): needSensorRunningLp, mCurrentAppOrientation =-1 I/WindowManager( 80): Enabling listeners W/ActivityThread(17738): Application com.ejf.convince.jenplus is waiting for the debugger on port 8100... I/System.out(17738): Sending WAIT chunk I/dalvikvm(17738): Debugger is active I/AlertDialog( 80): [onCreate] auto launch SIP. I/WindowManager( 80): onOrientationChanged, rotation changed to 0 I/System.out(17738): Debugger has connected I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): waiting for debugger to settle... I/System.out(17738): debugger has settled (1370) I/ActivityManager( 80): Displayed activity com.ejf.convince.jenplus/.JenPLUS: 5186 ms I/OpenCore( 2696): [Hank debug] LN 289 FN CreateNode I/AudioHardwareMSM72XX( 2696): AUDIO_START: start kernel pcm_out driver. W/AudioFlinger( 2696): write blocked for 96 msecs I/PlayerDriver( 2696): CIQ 1625 sendEvent state=5 I/OpenCore( 2696): [Hank debug] LN 289 FN CreateNode I/PlayerDriver( 2696): CIQ 1625 sendEvent state=5 I/OpenCore( 2696): [Hank debug] LN 289 FN CreateNode I/PlayerDriver( 2696): CIQ 1625 sendEvent state=5 I/OpenCore( 2696): [Hank debug] LN 289 FN CreateNode I/PlayerDriver( 2696): CIQ 1625 sendEvent state=5 W/AuthorDriver( 2696): Intended width(640) exceeds the max allowed width(352). Max width is used instead. W/AuthorDriver( 2696): Intended height(480) exceeds the max allowed height(288). Max height is used instead. I/AudioHardwareMSM72XX( 2696): AudioHardware pcm playback is going to standby. I/DEBUG (16094): *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** I/DEBUG (16094): Build fingerprint: 'sprint/htc_heroc/heroc/heroc: 1.5/CUPCAKE/85027:user/release-keys' I/DEBUG (16094): pid: 17738, tid: 17738 com.ejf.convince.jenplus Thanks in advance! -- Don Wilde http://www.ConvinceProject.com

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  • PHP mtChart (new pChart): how do i control the angle of x-axis labels?

    - by gsquare567
    i am trying to graph the results of a survey, where the question is multiple choice. eg. How would you describe this website? format: option | number of times selected | percentage of users who selected that option Informative 1 50% All of the above 1 50% Interesting 0 0% Intelligent 0 0% Cool 0 0% Incredible 0 0% Sleek 0 0% Amazing the graph is a bar graph, where each bar represents one of those options, and the height of the bar depends on the number of times selected. however, the labels are slanted at a 45 degree angle and are barely readable! here is my code: <?php require_once ("includes/common.php"); require_once ("graph/mtChart.min.php"); // type must be specified $type = $_GET['type']; if($type == "surveys_report_MC_or_CB") { // PARAMS $surveyID = $_GET['surveyID']; $questionID = $_GET['questionID']; // END PARAMS $question = SurveyQuestions::getSingle($questionID); $answers = SurveyAnswers::getAll($questionID); $options = SurveyQuestionOptions::getAll($question[SurveyQuestions::surveyQuestionID]); $others = SurveyAnswers::setOptionCounts($options, $answers); $printedOthers = false; // set graph $values = array(); $axisLabels = array(); foreach($options as $option) { $values[$option[SurveyQuestionOptions::optionText]] = $option['count']; $axisLabels[] = $option[SurveyQuestionOptions::optionText]; } $graphs = array(); $graphs[0] = $values; $xName = "Option"; $yName = "Number of Times Selected"; $graphTitle = $question[SurveyQuestions::question]; $series = array("Total"); $showLegend = false; $tall = false; } drawGraph($graphs, $axisLabels, $xName, $yName, $graphTitle, $series, $showLegend, $tall); function drawGraph($graphs, $axisLabels, $xName, $yName, $graphTitle, $series, $showLegend, $tall) { $Graph = ($tall) ? new mtChart(575,375) : new mtChart(575,275); // Dataset definition $avg = 0; $i = 0; foreach ($graphs as $key => $value) { $Graph->AddPoint($value,"series" . $key); $Graph->SetSerieName($series[$key],"series" . $key); // Get average $avg += array_sum($value); $size = sizeof($value); $i += $size; // Calculate x-axis tick interval $step = ceil($size / 25); } $Graph->AddPoint($axisLabels,"XLabel"); $Graph->AddAllSeries(); $Graph->RemoveSerie("XLabel"); $Graph->SetAbsciseLabelSerie("XLabel"); $Graph->SetXAxisName($xName); $Graph->SetYAxisName($yName); // Get from cache if it exists $Graph->enableCaching(NULL, 'graph/cache/'); $Graph->GetFromCache(); // Initialize the graph $Graph->setInterval($step); $Graph->setFontProperties("graph/tahoma.ttf",8); ($showLegend) ? $Graph->setGraphArea(45,30,475,200) : $Graph->setGraphArea(75,30,505,200); $Graph->drawGraphArea(255,255,255,TRUE); $Graph->drawScale(SCALE_START0,100,100,100,TRUE,55,1,TRUE); $Graph->drawGrid(4,TRUE,230,230,230,50); // Draw the 0 line $Graph->setFontProperties("graph/tahoma.ttf",6); $Graph->drawTreshold(0,143,55,72,TRUE,TRUE); // Draw the bar graph $Graph->drawBarGraph(); // Draw average line $Graph->drawTreshold($avg/$i, 0, 0, 0, FALSE, FALSE, 5); // Finish the graph $Graph->setFontProperties("graph/tahoma.ttf",8); if ($showLegend) { $Graph->drawLegend(482,30,255,255,255,255,255,255,100,100,100); } $Graph->setFontProperties("graph/tahoma.ttf",10); $Graph->drawTitle(0,22,$graphTitle,100,100,100,555); // Draw Graph $Graph->Stroke(); } and here is where i use it on the page: <div class="graph_container"> <img src="drawGraph.php?type=surveys_report_MC_or_CB&surveyID=<?php echo $survey[Surveys::surveyID] ?>&questionID=<?php echo $question[SurveyQuestions::surveyQuestionID] ?>" /> is there a setting i can apply to the graph which will make the text look nicer, or at least let me set the angle to 90 degrees so people can read it if they cock their head to the left? thanks! btw, mtchart is located here: http://code.google.com/p/mtchart/ and pchart (the original, which has mainly the same code) is here: http://pchart.sourceforge.net/documentation.php

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  • Looking for a better way to integrate a static list into a set of classes

    - by EvilTeach
    I'm trying to expand my sons interest from Warcraft 3 programming into C++ to broaden his horizons to a degree. We are planning on porting a little game that he wrote. The context goes something like this. There are Ships and Missiles, for which Ships will use Missiles and interact with them A Container exists which will hold 'a list' of ships. A Container exists which will hold 'a list' of planets. One can apply a function over all elements in the Container (for_each) Ships and Missles can be created/destroyed at any time New objects automatically insert themselves into the proper container. I cobbled a small example together to do that job, so we can talk about topics (list, templates etc) but I am not pleased with the results. #include <iostream> #include <list> using namespace std; /* Base class to hold static list in common with various object groups */ template<class T> class ObjectManager { public : ObjectManager ( void ) { cout << "Construct ObjectManager at " << this << endl; objectList.push_back(this); } virtual ~ObjectManager ( void ) { cout << "Destroy ObjectManager at " << this << endl; } void for_each ( void (*function)(T *) ) { for (objectListIter = objectList.begin(); objectListIter != objectList.end(); ++objectListIter) { (*function)((T *) *objectListIter); } } list<ObjectManager<T> *>::iterator objectListIter; static list<ObjectManager<T> *> objectList; }; /* initializer for static list */ template<class T> list<ObjectManager<T> *> ObjectManager<T>::objectList; /* A simple ship for testing */ class Ship : public ObjectManager<Ship> { public : Ship ( void ) : ObjectManager<Ship>() { cout << "Construct Ship at " << this << endl; } ~Ship ( void ) { cout << "Destroy Ship at " << this << endl; } friend ostream &operator<< ( ostream &out, const Ship &that ) { out << "I am a ship"; return out; } }; /* A simple missile for testing */ class Missile : public ObjectManager<Missile> { public : Missile ( void ) : ObjectManager<Missile>() { cout << "Construct Missile at " << this << endl; } ~Missile ( void ) { cout << "Destroy Missile at " << this << endl; } friend ostream &operator<< ( ostream &out, const Missile &that ) { out << "I am a missile"; return out; } }; /* A function suitable for the for_each function */ template <class T> void show ( T *it ) { cout << "Show: " << *it << " at " << it << endl; } int main ( void ) { /* Create dummy planets for testing */ Missile p1; Missile p2; /* Demonstrate Iterator */ p1.for_each(show); /* Create dummy ships for testing */ Ship s1; Ship s2; Ship s3; /* Demonstrate Iterator */ s1.for_each(show); return 0; } Specifically, The list is effectively embedded in each ship though the inheritance mechanism. One must have a ship, in order to access the list of ships. One must have a missile in order to be able to access the list of missiles. That feels awkward. My question boils down to "Is there a better way to do this?" Automatic object container creation Automatic object insertion Container access without requiring an object in the list to access it. I am looking for better ideas. All helpful entries get an upvote. Thanks Evil.

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  • Test of procedure is fine but when called from a menu gives uninitialized errors. C

    - by Delfic
    The language is portuguese, but I think you get the picture. My main calls only the menu function (the function in comment is the test which works). In the menu i introduce the option 1 which calls the same function. But there's something wrong. If i test it solely on the input: (1/1)x^2 //it reads the polinomyal (2/1) //reads the rational and returns 4 (you can guess what it does, calculates the value of an instace of x over a rational) My polinomyals are linear linked lists with a coeficient (rational) and a degree (int) int main () { menu_interactivo (); // instanciacao (); return 0; } void menu_interactivo(void) { int i; do{ printf("1. Instanciacao de um polinomio com um escalar\n"); printf("2. Multiplicacao de um polinomio por um escalar\n"); printf("3. Soma de dois polinomios\n"); printf("4. Multiplicacao de dois polinomios\n"); printf("5. Divisao de dois polinomios\n"); printf("0. Sair\n"); scanf ("%d", &i); switch (i) { case 0: exit(0); break; case 1: instanciacao (); break; case 2: multiplicacao_esc (); break; case 3: somar_pol (); break; case 4: multiplicacao_pol (); break; case 5: divisao_pol (); break; default:printf("O numero introduzido nao e valido!\n"); } } while (i != 0); } When i call it with the menu, with the same input, it does not stop reading the polinomyal (I know this because it does not ask me for the rational as on the other example) I've run it with valgrind --track-origins=yes returning the following: ==17482== Memcheck, a memory error detector ==17482== Copyright (C) 2002-2009, and GNU GPL'd, by Julian Seward et al. ==17482== Using Valgrind-3.5.0 and LibVEX; rerun with -h for copyright info ==17482== Command: ./teste ==17482== 1. Instanciacao de um polinomio com um escalar 2. Multiplicacao de um polinomio por um escalar 3. Soma de dois polinomios 4. Multiplicacao de dois polinomios 5. Divisao de dois polinomios 0. Sair 1 Introduza um polinomio na forma (n0/d0)x^e0 + (n1/d1)x^e1 + ... + (nk/dk)^ek, com ei > e(i+1): (1/1)x^2 ==17482== Conditional jump or move depends on uninitialised value(s) ==17482== at 0x401126: simplifica_f (fraccoes.c:53) ==17482== by 0x4010CB: le_f (fraccoes.c:30) ==17482== by 0x400CDA: le_pol (polinomios.c:156) ==17482== by 0x400817: instanciacao (t4.c:14) ==17482== by 0x40098C: menu_interactivo (t4.c:68) ==17482== by 0x4009BF: main (t4.c:86) ==17482== Uninitialised value was created by a stack allocation ==17482== at 0x401048: le_f (fraccoes.c:19) ==17482== ==17482== Conditional jump or move depends on uninitialised value(s) ==17482== at 0x400D03: le_pol (polinomios.c:163) ==17482== by 0x400817: instanciacao (t4.c:14) ==17482== by 0x40098C: menu_interactivo (t4.c:68) ==17482== by 0x4009BF: main (t4.c:86) ==17482== Uninitialised value was created by a stack allocation ==17482== at 0x401048: le_f (fraccoes.c:19) ==17482== I will now give you the functions which are called void le_pol (pol *p) { fraccao f; int e; char c; printf ("Introduza um polinomio na forma (n0/d0)x^e0 + (n1/d1)x^e1 + ... + (nk/dk)^ek,\n"); printf("com ei > e(i+1):\n"); *p = NULL; do { le_f (&f); getchar(); getchar(); scanf ("%d", &e); if (f.n != 0) *p = add (*p, f, e); c = getchar (); if (c != '\n') { getchar(); getchar(); } } while (c != '\n'); } void instanciacao (void) { pol p1; fraccao f; le_pol (&p1); printf ("Insira uma fraccao na forma (n/d):\n"); le_f (&f); escreve_f(inst_esc_pol(p1, f)); } void le_f (fraccao *f) { int n, d; getchar (); scanf ("%d", &n); getchar (); scanf ("%d", &d); getchar (); assert (d != 0); *f = simplifica_f(cria_f(n, d)); } simplifica_f simplifies a rational and cria_f creates a rationa given the numerator and the denominator Can someone help me please? Thanks in advance. If you want me to provide some tests, just post it. See ya.

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  • Improving Partitioned Table Join Performance

    - by Paul White
    The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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  • C#/.NET Little Wonders: The Concurrent Collections (1 of 3)

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  In the next few weeks, we will discuss the concurrent collections and how they have changed the face of concurrent programming. This week’s post will begin with a general introduction and discuss the ConcurrentStack<T> and ConcurrentQueue<T>.  Then in the following post we’ll discuss the ConcurrentDictionary<T> and ConcurrentBag<T>.  Finally, we shall close on the third post with a discussion of the BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. A brief history of collections In the beginning was the .NET 1.0 Framework.  And out of this framework emerged the System.Collections namespace, and it was good.  It contained all the basic things a growing programming language needs like the ArrayList and Hashtable collections.  The main problem, of course, with these original collections is that they held items of type object which means you had to be disciplined enough to use them correctly or you could end up with runtime errors if you got an object of a type you weren't expecting. Then came .NET 2.0 and generics and our world changed forever!  With generics the C# language finally got an equivalent of the very powerful C++ templates.  As such, the System.Collections.Generic was born and we got type-safe versions of all are favorite collections.  The List<T> succeeded the ArrayList and the Dictionary<TKey,TValue> succeeded the Hashtable and so on.  The new versions of the library were not only safer because they checked types at compile-time, in many cases they were more performant as well.  So much so that it's Microsoft's recommendation that the System.Collections original collections only be used for backwards compatibility. So we as developers came to know and love the generic collections and took them into our hearts and embraced them.  The problem is, thread safety in both the original collections and the generic collections can be problematic, for very different reasons. Now, if you are only doing single-threaded development you may not care – after all, no locking is required.  Even if you do have multiple threads, if a collection is “load-once, read-many” you don’t need to do anything to protect that container from multi-threaded access, as illustrated below: 1: public static class OrderTypeTranslator 2: { 3: // because this dictionary is loaded once before it is ever accessed, we don't need to synchronize 4: // multi-threaded read access 5: private static readonly Dictionary<string, char> _translator = new Dictionary<string, char> 6: { 7: {"New", 'N'}, 8: {"Update", 'U'}, 9: {"Cancel", 'X'} 10: }; 11:  12: // the only public interface into the dictionary is for reading, so inherently thread-safe 13: public static char? Translate(string orderType) 14: { 15: char charValue; 16: if (_translator.TryGetValue(orderType, out charValue)) 17: { 18: return charValue; 19: } 20:  21: return null; 22: } 23: } Unfortunately, most of our computer science problems cannot get by with just single-threaded applications or with multi-threading in a load-once manner.  Looking at  today's trends, it's clear to see that computers are not so much getting faster because of faster processor speeds -- we've nearly reached the limits we can push through with today's technologies -- but more because we're adding more cores to the boxes.  With this new hardware paradigm, it is even more important to use multi-threaded applications to take full advantage of parallel processing to achieve higher application speeds. So let's look at how to use collections in a thread-safe manner. Using historical collections in a concurrent fashion The early .NET collections (System.Collections) had a Synchronized() static method that could be used to wrap the early collections to make them completely thread-safe.  This paradigm was dropped in the generic collections (System.Collections.Generic) because having a synchronized wrapper resulted in atomic locks for all operations, which could prove overkill in many multithreading situations.  Thus the paradigm shifted to having the user of the collection specify their own locking, usually with an external object: 1: public class OrderAggregator 2: { 3: private static readonly Dictionary<string, List<Order>> _orders = new Dictionary<string, List<Order>>(); 4: private static readonly _orderLock = new object(); 5:  6: public void Add(string accountNumber, Order newOrder) 7: { 8: List<Order> ordersForAccount; 9:  10: // a complex operation like this should all be protected 11: lock (_orderLock) 12: { 13: if (!_orders.TryGetValue(accountNumber, out ordersForAccount)) 14: { 15: _orders.Add(accountNumber, ordersForAccount = new List<Order>()); 16: } 17:  18: ordersForAccount.Add(newOrder); 19: } 20: } 21: } Notice how we’re performing several operations on the dictionary under one lock.  With the Synchronized() static methods of the early collections, you wouldn’t be able to specify this level of locking (a more macro-level).  So in the generic collections, it was decided that if a user needed synchronization, they could implement their own locking scheme instead so that they could provide synchronization as needed. The need for better concurrent access to collections Here’s the problem: it’s relatively easy to write a collection that locks itself down completely for access, but anything more complex than that can be difficult and error-prone to write, and much less to make it perform efficiently!  For example, what if you have a Dictionary that has frequent reads but in-frequent updates?  Do you want to lock down the entire Dictionary for every access?  This would be overkill and would prevent concurrent reads.  In such cases you could use something like a ReaderWriterLockSlim which allows for multiple readers in a lock, and then once a writer grabs the lock it blocks all further readers until the writer is done (in a nutshell).  This is all very complex stuff to consider. Fortunately, this is where the Concurrent Collections come in.  The Parallel Computing Platform team at Microsoft went through great pains to determine how to make a set of concurrent collections that would have the best performance characteristics for general case multi-threaded use. Now, as in all things involving threading, you should always make sure you evaluate all your container options based on the particular usage scenario and the degree of parallelism you wish to acheive. This article should not be taken to understand that these collections are always supperior to the generic collections. Each fills a particular need for a particular situation. Understanding what each container is optimized for is key to the success of your application whether it be single-threaded or multi-threaded. General points to consider with the concurrent collections The MSDN points out that the concurrent collections all support the ICollection interface. However, since the collections are already synchronized, the IsSynchronized property always returns false, and SyncRoot always returns null.  Thus you should not attempt to use these properties for synchronization purposes. Note that since the concurrent collections also may have different operations than the traditional data structures you may be used to.  Now you may ask why they did this, but it was done out of necessity to keep operations safe and atomic.  For example, in order to do a Pop() on a stack you have to know the stack is non-empty, but between the time you check the stack’s IsEmpty property and then do the Pop() another thread may have come in and made the stack empty!  This is why some of the traditional operations have been changed to make them safe for concurrent use. In addition, some properties and methods in the concurrent collections achieve concurrency by creating a snapshot of the collection, which means that some operations that were traditionally O(1) may now be O(n) in the concurrent models.  I’ll try to point these out as we talk about each collection so you can be aware of any potential performance impacts.  Finally, all the concurrent containers are safe for enumeration even while being modified, but some of the containers support this in different ways (snapshot vs. dirty iteration).  Once again I’ll highlight how thread-safe enumeration works for each collection. ConcurrentStack<T>: The thread-safe LIFO container The ConcurrentStack<T> is the thread-safe counterpart to the System.Collections.Generic.Stack<T>, which as you may remember is your standard last-in-first-out container.  If you think of algorithms that favor stack usage (for example, depth-first searches of graphs and trees) then you can see how using a thread-safe stack would be of benefit. The ConcurrentStack<T> achieves thread-safe access by using System.Threading.Interlocked operations.  This means that the multi-threaded access to the stack requires no traditional locking and is very, very fast! For the most part, the ConcurrentStack<T> behaves like it’s Stack<T> counterpart with a few differences: Pop() was removed in favor of TryPop() Returns true if an item existed and was popped and false if empty. PushRange() and TryPopRange() were added Allows you to push multiple items and pop multiple items atomically. Count takes a snapshot of the stack and then counts the items. This means it is a O(n) operation, if you just want to check for an empty stack, call IsEmpty instead which is O(1). ToArray() and GetEnumerator() both also take snapshots. This means that iteration over a stack will give you a static view at the time of the call and will not reflect updates. Pushing on a ConcurrentStack<T> works just like you’d expect except for the aforementioned PushRange() method that was added to allow you to push a range of items concurrently. 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: // but you can also push multiple items in one atomic operation (no interleaves) 7: stack.PushRange(new [] { "Second", "Third", "Fourth" }); For looking at the top item of the stack (without removing it) the Peek() method has been removed in favor of a TryPeek().  This is because in order to do a peek the stack must be non-empty, but between the time you check for empty and the time you execute the peek the stack contents may have changed.  Thus the TryPeek() was created to be an atomic check for empty, and then peek if not empty: 1: // to look at top item of stack without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (stack.TryPeek(out item)) 5: { 6: Console.WriteLine("Top item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Stack was empty."); 11: } Finally, to remove items from the stack, we have the TryPop() for single, and TryPopRange() for multiple items.  Just like the TryPeek(), these operations replace Pop() since we need to ensure atomically that the stack is non-empty before we pop from it: 1: // to remove items, use TryPop or TryPopRange to get multiple items atomically (no interleaves) 2: if (stack.TryPop(out item)) 3: { 4: Console.WriteLine("Popped " + item); 5: } 6:  7: // TryPopRange will only pop up to the number of spaces in the array, the actual number popped is returned. 8: var poppedItems = new string[2]; 9: int numPopped = stack.TryPopRange(poppedItems); 10:  11: foreach (var theItem in poppedItems.Take(numPopped)) 12: { 13: Console.WriteLine("Popped " + theItem); 14: } Finally, note that as stated before, GetEnumerator() and ToArray() gets a snapshot of the data at the time of the call.  That means if you are enumerating the stack you will get a snapshot of the stack at the time of the call.  This is illustrated below: 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: var results = stack.GetEnumerator(); 7:  8: // but you can also push multiple items in one atomic operation (no interleaves) 9: stack.PushRange(new [] { "Second", "Third", "Fourth" }); 10:  11: while(results.MoveNext()) 12: { 13: Console.WriteLine("Stack only has: " + results.Current); 14: } The only item that will be printed out in the above code is "First" because the snapshot was taken before the other items were added. This may sound like an issue, but it’s really for safety and is more correct.  You don’t want to enumerate a stack and have half a view of the stack before an update and half a view of the stack after an update, after all.  In addition, note that this is still thread-safe, whereas iterating through a non-concurrent collection while updating it in the old collections would cause an exception. ConcurrentQueue<T>: The thread-safe FIFO container The ConcurrentQueue<T> is the thread-safe counterpart of the System.Collections.Generic.Queue<T> class.  The concurrent queue uses an underlying list of small arrays and lock-free System.Threading.Interlocked operations on the head and tail arrays.  Once again, this allows us to do thread-safe operations without the need for heavy locks! The ConcurrentQueue<T> (like the ConcurrentStack<T>) has some departures from the non-concurrent counterpart.  Most notably: Dequeue() was removed in favor of TryDequeue(). Returns true if an item existed and was dequeued and false if empty. Count does not take a snapshot It subtracts the head and tail index to get the count.  This results overall in a O(1) complexity which is quite good.  It’s still recommended, however, that for empty checks you call IsEmpty instead of comparing Count to zero. ToArray() and GetEnumerator() both take snapshots. This means that iteration over a queue will give you a static view at the time of the call and will not reflect updates. The Enqueue() method on the ConcurrentQueue<T> works much the same as the generic Queue<T>: 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5: queue.Enqueue("Second"); 6: queue.Enqueue("Third"); For front item access, the TryPeek() method must be used to attempt to see the first item if the queue.  There is no Peek() method since, as you’ll remember, we can only peek on a non-empty queue, so we must have an atomic TryPeek() that checks for empty and then returns the first item if the queue is non-empty. 1: // to look at first item in queue without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (queue.TryPeek(out item)) 5: { 6: Console.WriteLine("First item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Queue was empty."); 11: } Then, to remove items you use TryDequeue().  Once again this is for the same reason we have TryPeek() and not Peek(): 1: // to remove items, use TryDequeue. If queue is empty returns false. 2: if (queue.TryDequeue(out item)) 3: { 4: Console.WriteLine("Dequeued first item " + item); 5: } Just like the concurrent stack, the ConcurrentQueue<T> takes a snapshot when you call ToArray() or GetEnumerator() which means that subsequent updates to the queue will not be seen when you iterate over the results.  Thus once again the code below will only show the first item, since the other items were added after the snapshot. 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5:  6: var iterator = queue.GetEnumerator(); 7:  8: queue.Enqueue("Second"); 9: queue.Enqueue("Third"); 10:  11: // only shows First 12: while (iterator.MoveNext()) 13: { 14: Console.WriteLine("Dequeued item " + iterator.Current); 15: } Using collections concurrently You’ll notice in the examples above I stuck to using single-threaded examples so as to make them deterministic and the results obvious.  Of course, if we used these collections in a truly multi-threaded way the results would be less deterministic, but would still be thread-safe and with no locking on your part required! For example, say you have an order processor that takes an IEnumerable<Order> and handles each other in a multi-threaded fashion, then groups the responses together in a concurrent collection for aggregation.  This can be done easily with the TPL’s Parallel.ForEach(): 1: public static IEnumerable<OrderResult> ProcessOrders(IEnumerable<Order> orderList) 2: { 3: var proxy = new OrderProxy(); 4: var results = new ConcurrentQueue<OrderResult>(); 5:  6: // notice that we can process all these in parallel and put the results 7: // into our concurrent collection without needing any external locking! 8: Parallel.ForEach(orderList, 9: order => 10: { 11: var result = proxy.PlaceOrder(order); 12:  13: results.Enqueue(result); 14: }); 15:  16: return results; 17: } Summary Obviously, if you do not need multi-threaded safety, you don’t need to use these collections, but when you do need multi-threaded collections these are just the ticket! The plethora of features (I always think of the movie The Three Amigos when I say plethora) built into these containers and the amazing way they acheive thread-safe access in an efficient manner is wonderful to behold. Stay tuned next week where we’ll continue our discussion with the ConcurrentBag<T> and the ConcurrentDictionary<TKey,TValue>. For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this wonderful whitepaper by the Microsoft Parallel Computing Platform team here.   Tweet Technorati Tags: C#,.NET,Concurrent Collections,Collections,Multi-Threading,Little Wonders,BlackRabbitCoder,James Michael Hare

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  • Using TPL and PLINQ to raise performance of feed aggregator

    - by DigiMortal
    In this posting I will show you how to use Task Parallel Library (TPL) and PLINQ features to boost performance of simple RSS-feed aggregator. I will use here only very basic .NET classes that almost every developer starts from when learning parallel programming. Of course, we will also measure how every optimization affects performance of feed aggregator. Feed aggregator Our feed aggregator works as follows: Load list of blogs Download RSS-feed Parse feed XML Add new posts to database Our feed aggregator is run by task scheduler after every 15 minutes by example. We will start our journey with serial implementation of feed aggregator. Second step is to use task parallelism and parallelize feeds downloading and parsing. And our last step is to use data parallelism to parallelize database operations. We will use Stopwatch class to measure how much time it takes for aggregator to download and insert all posts from all registered blogs. After every run we empty posts table in database. Serial aggregation Before doing parallel stuff let’s take a look at serial implementation of feed aggregator. All tasks happen one after other. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();           for (var index = 0; index <blogs.Count; index++)         {              ImportFeed(blogs[index]);         }     }       private void ImportFeed(BlogDto blog)     {         if(blog == null)             return;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                 }       private void ImportRssFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = RssFeed.Create(uri);           foreach (var item in feed.Channel.Items)         {             SaveRssFeedItem(item, blog.Id, blog.CreatedById);         }     }       private void ImportAtomFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           foreach (var item in feed.Entries)         {             SaveAtomFeedEntry(item, blog.Id, blog.CreatedById);         }     } } Serial implementation of feed aggregator downloads and inserts all posts with 25.46 seconds. Task parallelism Task parallelism means that separate tasks are run in parallel. You can find out more about task parallelism from MSDN page Task Parallelism (Task Parallel Library) and Wikipedia page Task parallelism. Although finding parts of code that can run safely in parallel without synchronization issues is not easy task we are lucky this time. Feeds import and parsing is perfect candidate for parallel tasks. We can safely parallelize feeds import because importing tasks doesn’t share any resources and therefore they don’t also need any synchronization. After getting the list of blogs we iterate through the collection and start new TPL task for each blog feed aggregation. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();                var tasks = new Task[blogs.Count];           for (var index = 0; index <blogs.Count; index++)         {             tasks[index] = new Task(ImportFeed, blogs[index]);             tasks[index].Start();         }           Task.WaitAll(tasks);     }       private void ImportFeed(object blogObject)     {         if(blogObject == null)             return;         var blog = (BlogDto)blogObject;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                }       private void ImportRssFeed(BlogDto blog)     {          var uri = new Uri(blog.RssUrl);          var feed = RssFeed.Create(uri);           foreach (var item in feed.Channel.Items)          {              SaveRssFeedItem(item, blog.Id, blog.CreatedById);          }     }     private void ImportAtomFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           foreach (var item in feed.Entries)         {             SaveAtomFeedEntry(item, blog.Id, blog.CreatedById);         }     } } You should notice first signs of the power of TPL. We made only minor changes to our code to parallelize blog feeds aggregating. On my machine this modification gives some performance boost – time is now 17.57 seconds. Data parallelism There is one more way how to parallelize activities. Previous section introduced task or operation based parallelism, this section introduces data based parallelism. By MSDN page Data Parallelism (Task Parallel Library) data parallelism refers to scenario in which the same operation is performed concurrently on elements in a source collection or array. In our code we have independent collections we can process in parallel – imported feed entries. As checking for feed entry existence and inserting it if it is missing from database doesn’t affect other entries the imported feed entries collection is ideal candidate for parallelization. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();                var tasks = new Task[blogs.Count];           for (var index = 0; index <blogs.Count; index++)         {             tasks[index] = new Task(ImportFeed, blogs[index]);             tasks[index].Start();         }           Task.WaitAll(tasks);     }       private void ImportFeed(object blogObject)     {         if(blogObject == null)             return;         var blog = (BlogDto)blogObject;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                }       private void ImportRssFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = RssFeed.Create(uri);           feed.Channel.Items.AsParallel().ForAll(a =>         {             SaveRssFeedItem(a, blog.Id, blog.CreatedById);         });      }        private void ImportAtomFeed(BlogDto blog)      {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           feed.Entries.AsParallel().ForAll(a =>         {              SaveAtomFeedEntry(a, blog.Id, blog.CreatedById);         });      } } We did small change again and as the result we parallelized checking and saving of feed items. This change was data centric as we applied same operation to all elements in collection. On my machine I got better performance again. Time is now 11.22 seconds. Results Let’s visualize our measurement results (numbers are given in seconds). As we can see then with task parallelism feed aggregation takes about 25% less time than in original case. When adding data parallelism to task parallelism our aggregation takes about 2.3 times less time than in original case. More about TPL and PLINQ Adding parallelism to your application can be very challenging task. You have to carefully find out parts of your code where you can safely go to parallel processing and even then you have to measure the effects of parallel processing to find out if parallel code performs better. If you are not careful then troubles you will face later are worse than ones you have seen before (imagine error that occurs by average only once per 10000 code runs). Parallel programming is something that is hard to ignore. Effective programs are able to use multiple cores of processors. Using TPL you can also set degree of parallelism so your application doesn’t use all computing cores and leaves one or more of them free for host system and other processes. And there are many more things in TPL that make it easier for you to start and go on with parallel programming. In next major version all .NET languages will have built-in support for parallel programming. There will be also new language constructs that support parallel programming. Currently you can download Visual Studio Async to get some idea about what is coming. Conclusion Parallel programming is very challenging but good tools offered by Visual Studio and .NET Framework make it way easier for us. In this posting we started with feed aggregator that imports feed items on serial mode. With two steps we parallelized feed importing and entries inserting gaining 2.3 times raise in performance. Although this number is specific to my test environment it shows clearly that parallel programming may raise the performance of your application significantly.

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  • PTLQueue : a scalable bounded-capacity MPMC queue

    - by Dave
    Title: Fast concurrent MPMC queue -- I've used the following concurrent queue algorithm enough that it warrants a blog entry. I'll sketch out the design of a fast and scalable multiple-producer multiple-consumer (MPSC) concurrent queue called PTLQueue. The queue has bounded capacity and is implemented via a circular array. Bounded capacity can be a useful property if there's a mismatch between producer rates and consumer rates where an unbounded queue might otherwise result in excessive memory consumption by virtue of the container nodes that -- in some queue implementations -- are used to hold values. A bounded-capacity queue can provide flow control between components. Beware, however, that bounded collections can also result in resource deadlock if abused. The put() and take() operators are partial and wait for the collection to become non-full or non-empty, respectively. Put() and take() do not allocate memory, and are not vulnerable to the ABA pathologies. The PTLQueue algorithm can be implemented equally well in C/C++ and Java. Partial operators are often more convenient than total methods. In many use cases if the preconditions aren't met, there's nothing else useful the thread can do, so it may as well wait via a partial method. An exception is in the case of work-stealing queues where a thief might scan a set of queues from which it could potentially steal. Total methods return ASAP with a success-failure indication. (It's tempting to describe a queue or API as blocking or non-blocking instead of partial or total, but non-blocking is already an overloaded concurrency term. Perhaps waiting/non-waiting or patient/impatient might be better terms). It's also trivial to construct partial operators by busy-waiting via total operators, but such constructs may be less efficient than an operator explicitly and intentionally designed to wait. A PTLQueue instance contains an array of slots, where each slot has volatile Turn and MailBox fields. The array has power-of-two length allowing mod/div operations to be replaced by masking. We assume sensible padding and alignment to reduce the impact of false sharing. (On x86 I recommend 128-byte alignment and padding because of the adjacent-sector prefetch facility). Each queue also has PutCursor and TakeCursor cursor variables, each of which should be sequestered as the sole occupant of a cache line or sector. You can opt to use 64-bit integers if concerned about wrap-around aliasing in the cursor variables. Put(null) is considered illegal, but the caller or implementation can easily check for and convert null to a distinguished non-null proxy value if null happens to be a value you'd like to pass. Take() will accordingly convert the proxy value back to null. An advantage of PTLQueue is that you can use atomic fetch-and-increment for the partial methods. We initialize each slot at index I with (Turn=I, MailBox=null). Both cursors are initially 0. All shared variables are considered "volatile" and atomics such as CAS and AtomicFetchAndIncrement are presumed to have bidirectional fence semantics. Finally T is the templated type. I've sketched out a total tryTake() method below that allows the caller to poll the queue. tryPut() has an analogous construction. Zebra stripping : alternating row colors for nice-looking code listings. See also google code "prettify" : https://code.google.com/p/google-code-prettify/ Prettify is a javascript module that yields the HTML/CSS/JS equivalent of pretty-print. -- pre:nth-child(odd) { background-color:#ff0000; } pre:nth-child(even) { background-color:#0000ff; } border-left: 11px solid #ccc; margin: 1.7em 0 1.7em 0.3em; background-color:#BFB; font-size:12px; line-height:65%; " // PTLQueue : Put(v) : // producer : partial method - waits as necessary assert v != null assert Mask = 1 && (Mask & (Mask+1)) == 0 // Document invariants // doorway step // Obtain a sequence number -- ticket // As a practical concern the ticket value is temporally unique // The ticket also identifies and selects a slot auto tkt = AtomicFetchIncrement (&PutCursor, 1) slot * s = &Slots[tkt & Mask] // waiting phase : // wait for slot's generation to match the tkt value assigned to this put() invocation. // The "generation" is implicitly encoded as the upper bits in the cursor // above those used to specify the index : tkt div (Mask+1) // The generation serves as an epoch number to identify a cohort of threads // accessing disjoint slots while s-Turn != tkt : Pause assert s-MailBox == null s-MailBox = v // deposit and pass message Take() : // consumer : partial method - waits as necessary auto tkt = AtomicFetchIncrement (&TakeCursor,1) slot * s = &Slots[tkt & Mask] // 2-stage waiting : // First wait for turn for our generation // Acquire exclusive "take" access to slot's MailBox field // Then wait for the slot to become occupied while s-Turn != tkt : Pause // Concurrency in this section of code is now reduced to just 1 producer thread // vs 1 consumer thread. // For a given queue and slot, there will be most one Take() operation running // in this section. // Consumer waits for producer to arrive and make slot non-empty // Extract message; clear mailbox; advance Turn indicator // We have an obvious happens-before relation : // Put(m) happens-before corresponding Take() that returns that same "m" for T v = s-MailBox if v != null : s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 // unlock slot to admit next producer and consumer return v Pause tryTake() : // total method - returns ASAP with failure indication for auto tkt = TakeCursor slot * s = &Slots[tkt & Mask] if s-Turn != tkt : return null T v = s-MailBox // presumptive return value if v == null : return null // ratify tkt and v values and commit by advancing cursor if CAS (&TakeCursor, tkt, tkt+1) != tkt : continue s-MailBox = null ST-ST barrier s-Turn = tkt + Mask + 1 return v The basic idea derives from the Partitioned Ticket Lock "PTL" (US20120240126-A1) and the MultiLane Concurrent Bag (US8689237). The latter is essentially a circular ring-buffer where the elements themselves are queues or concurrent collections. You can think of the PTLQueue as a partitioned ticket lock "PTL" augmented to pass values from lock to unlock via the slots. Alternatively, you could conceptualize of PTLQueue as a degenerate MultiLane bag where each slot or "lane" consists of a simple single-word MailBox instead of a general queue. Each lane in PTLQueue also has a private Turn field which acts like the Turn (Grant) variables found in PTL. Turn enforces strict FIFO ordering and restricts concurrency on the slot mailbox field to at most one simultaneous put() and take() operation. PTL uses a single "ticket" variable and per-slot Turn (grant) fields while MultiLane has distinct PutCursor and TakeCursor cursors and abstract per-slot sub-queues. Both PTL and MultiLane advance their cursor and ticket variables with atomic fetch-and-increment. PTLQueue borrows from both PTL and MultiLane and has distinct put and take cursors and per-slot Turn fields. Instead of a per-slot queues, PTLQueue uses a simple single-word MailBox field. PutCursor and TakeCursor act like a pair of ticket locks, conferring "put" and "take" access to a given slot. PutCursor, for instance, assigns an incoming put() request to a slot and serves as a PTL "Ticket" to acquire "put" permission to that slot's MailBox field. To better explain the operation of PTLQueue we deconstruct the operation of put() and take() as follows. Put() first increments PutCursor obtaining a new unique ticket. That ticket value also identifies a slot. Put() next waits for that slot's Turn field to match that ticket value. This is tantamount to using a PTL to acquire "put" permission on the slot's MailBox field. Finally, having obtained exclusive "put" permission on the slot, put() stores the message value into the slot's MailBox. Take() similarly advances TakeCursor, identifying a slot, and then acquires and secures "take" permission on a slot by waiting for Turn. Take() then waits for the slot's MailBox to become non-empty, extracts the message, and clears MailBox. Finally, take() advances the slot's Turn field, which releases both "put" and "take" access to the slot's MailBox. Note the asymmetry : put() acquires "put" access to the slot, but take() releases that lock. At any given time, for a given slot in a PTLQueue, at most one thread has "put" access and at most one thread has "take" access. This restricts concurrency from general MPMC to 1-vs-1. We have 2 ticket locks -- one for put() and one for take() -- each with its own "ticket" variable in the form of the corresponding cursor, but they share a single "Grant" egress variable in the form of the slot's Turn variable. Advancing the PutCursor, for instance, serves two purposes. First, we obtain a unique ticket which identifies a slot. Second, incrementing the cursor is the doorway protocol step to acquire the per-slot mutual exclusion "put" lock. The cursors and operations to increment those cursors serve double-duty : slot-selection and ticket assignment for locking the slot's MailBox field. At any given time a slot MailBox field can be in one of the following states: empty with no pending operations -- neutral state; empty with one or more waiting take() operations pending -- deficit; occupied with no pending operations; occupied with one or more waiting put() operations -- surplus; empty with a pending put() or pending put() and take() operations -- transitional; or occupied with a pending take() or pending put() and take() operations -- transitional. The partial put() and take() operators can be implemented with an atomic fetch-and-increment operation, which may confer a performance advantage over a CAS-based loop. In addition we have independent PutCursor and TakeCursor cursors. Critically, a put() operation modifies PutCursor but does not access the TakeCursor and a take() operation modifies the TakeCursor cursor but does not access the PutCursor. This acts to reduce coherence traffic relative to some other queue designs. It's worth noting that slow threads or obstruction in one slot (or "lane") does not impede or obstruct operations in other slots -- this gives us some degree of obstruction isolation. PTLQueue is not lock-free, however. The implementation above is expressed with polite busy-waiting (Pause) but it's trivial to implement per-slot parking and unparking to deschedule waiting threads. It's also easy to convert the queue to a more general deque by replacing the PutCursor and TakeCursor cursors with Left/Front and Right/Back cursors that can move either direction. Specifically, to push and pop from the "left" side of the deque we would decrement and increment the Left cursor, respectively, and to push and pop from the "right" side of the deque we would increment and decrement the Right cursor, respectively. We used a variation of PTLQueue for message passing in our recent OPODIS 2013 paper. ul { list-style:none; padding-left:0; padding:0; margin:0; margin-left:0; } ul#myTagID { padding: 0px; margin: 0px; list-style:none; margin-left:0;} -- -- There's quite a bit of related literature in this area. I'll call out a few relevant references: Wilson's NYU Courant Institute UltraComputer dissertation from 1988 is classic and the canonical starting point : Operating System Data Structures for Shared-Memory MIMD Machines with Fetch-and-Add. Regarding provenance and priority, I think PTLQueue or queues effectively equivalent to PTLQueue have been independently rediscovered a number of times. See CB-Queue and BNPBV, below, for instance. But Wilson's dissertation anticipates the basic idea and seems to predate all the others. Gottlieb et al : Basic Techniques for the Efficient Coordination of Very Large Numbers of Cooperating Sequential Processors Orozco et al : CB-Queue in Toward high-throughput algorithms on many-core architectures which appeared in TACO 2012. Meneghin et al : BNPVB family in Performance evaluation of inter-thread communication mechanisms on multicore/multithreaded architecture Dmitry Vyukov : bounded MPMC queue (highly recommended) Alex Otenko : US8607249 (highly related). John Mellor-Crummey : Concurrent queues: Practical fetch-and-phi algorithms. Technical Report 229, Department of Computer Science, University of Rochester Thomasson : FIFO Distributed Bakery Algorithm (very similar to PTLQueue). Scott and Scherer : Dual Data Structures I'll propose an optimization left as an exercise for the reader. Say we wanted to reduce memory usage by eliminating inter-slot padding. Such padding is usually "dark" memory and otherwise unused and wasted. But eliminating the padding leaves us at risk of increased false sharing. Furthermore lets say it was usually the case that the PutCursor and TakeCursor were numerically close to each other. (That's true in some use cases). We might still reduce false sharing by incrementing the cursors by some value other than 1 that is not trivially small and is coprime with the number of slots. Alternatively, we might increment the cursor by one and mask as usual, resulting in a logical index. We then use that logical index value to index into a permutation table, yielding an effective index for use in the slot array. The permutation table would be constructed so that nearby logical indices would map to more distant effective indices. (Open question: what should that permutation look like? Possibly some perversion of a Gray code or De Bruijn sequence might be suitable). As an aside, say we need to busy-wait for some condition as follows : "while C == 0 : Pause". Lets say that C is usually non-zero, so we typically don't wait. But when C happens to be 0 we'll have to spin for some period, possibly brief. We can arrange for the code to be more machine-friendly with respect to the branch predictors by transforming the loop into : "if C == 0 : for { Pause; if C != 0 : break; }". Critically, we want to restructure the loop so there's one branch that controls entry and another that controls loop exit. A concern is that your compiler or JIT might be clever enough to transform this back to "while C == 0 : Pause". You can sometimes avoid this by inserting a call to a some type of very cheap "opaque" method that the compiler can't elide or reorder. On Solaris, for instance, you could use :"if C == 0 : { gethrtime(); for { Pause; if C != 0 : break; }}". It's worth noting the obvious duality between locks and queues. If you have strict FIFO lock implementation with local spinning and succession by direct handoff such as MCS or CLH,then you can usually transform that lock into a queue. Hidden commentary and annotations - invisible : * And of course there's a well-known duality between queues and locks, but I'll leave that topic for another blog post. * Compare and contrast : PTLQ vs PTL and MultiLane * Equivalent : Turn; seq; sequence; pos; position; ticket * Put = Lock; Deposit Take = identify and reserve slot; wait; extract & clear; unlock * conceptualize : Distinct PutLock and TakeLock implemented as ticket lock or PTL Distinct arrival cursors but share per-slot "Turn" variable provides exclusive role-based access to slot's mailbox field put() acquires exclusive access to a slot for purposes of "deposit" assigns slot round-robin and then acquires deposit access rights/perms to that slot take() acquires exclusive access to slot for purposes of "withdrawal" assigns slot round-robin and then acquires withdrawal access rights/perms to that slot At any given time, only one thread can have withdrawal access to a slot at any given time, only one thread can have deposit access to a slot Permissible for T1 to have deposit access and T2 to simultaneously have withdrawal access * round-robin for the purposes of; role-based; access mode; access role mailslot; mailbox; allocate/assign/identify slot rights; permission; license; access permission; * PTL/Ticket hybrid Asymmetric usage ; owner oblivious lock-unlock pairing K-exclusion add Grant cursor pass message m from lock to unlock via Slots[] array Cursor performs 2 functions : + PTL ticket + Assigns request to slot in round-robin fashion Deconstruct protocol : explication put() : allocate slot in round-robin fashion acquire PTL for "put" access store message into slot associated with PTL index take() : Acquire PTL for "take" access // doorway step seq = fetchAdd (&Grant, 1) s = &Slots[seq & Mask] // waiting phase while s-Turn != seq : pause Extract : wait for s-mailbox to be full v = s-mailbox s-mailbox = null Release PTL for both "put" and "take" access s-Turn = seq + Mask + 1 * Slot round-robin assignment and lock "doorway" protocol leverage the same cursor and FetchAdd operation on that cursor FetchAdd (&Cursor,1) + round-robin slot assignment and dispersal + PTL/ticket lock "doorway" step waiting phase is via "Turn" field in slot * PTLQueue uses 2 cursors -- put and take. Acquire "put" access to slot via PTL-like lock Acquire "take" access to slot via PTL-like lock 2 locks : put and take -- at most one thread can access slot's mailbox Both locks use same "turn" field Like multilane : 2 cursors : put and take slot is simple 1-capacity mailbox instead of queue Borrow per-slot turn/grant from PTL Provides strict FIFO Lock slot : put-vs-put take-vs-take at most one put accesses slot at any one time at most one put accesses take at any one time reduction to 1-vs-1 instead of N-vs-M concurrency Per slot locks for put/take Release put/take by advancing turn * is instrumental in ... * P-V Semaphore vs lock vs K-exclusion * See also : FastQueues-excerpt.java dice-etc/queue-mpmc-bounded-blocking-circular-xadd/ * PTLQueue is the same as PTLQB - identical * Expedient return; ASAP; prompt; immediately * Lamport's Bakery algorithm : doorway step then waiting phase Threads arriving at doorway obtain a unique ticket number Threads enter in ticket order * In the terminology of Reed and Kanodia a ticket lock corresponds to the busy-wait implementation of a semaphore using an eventcount and a sequencer It can also be thought of as an optimization of Lamport's bakery lock was designed for fault-tolerance rather than performance Instead of spinning on the release counter, processors using a bakery lock repeatedly examine the tickets of their peers --

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  • Large Object Heap Fragmentation

    - by Paul Ruane
    The C#/.NET application I am working on is suffering from a slow memory leak. I have used CDB with SOS to try to determine what is happening but the data does not seem to make any sense so I was hoping one of you may have experienced this before. The application is running on the 64 bit framework. It is continuously calculating and serialising data to a remote host and is hitting the Large Object Heap (LOH) a fair bit. However, most of the LOH objects I expect to be transient: once the calculation is complete and has been sent to the remote host, the memory should be freed. What I am seeing, however, is a large number of (live) object arrays interleaved with free blocks of memory, e.g., taking a random segment from the LOH: 0:000> !DumpHeap 000000005b5b1000 000000006351da10 Address MT Size ... 000000005d4f92e0 0000064280c7c970 16147872 000000005e45f880 00000000001661d0 1901752 Free 000000005e62fd38 00000642788d8ba8 1056 <-- 000000005e630158 00000000001661d0 5988848 Free 000000005ebe6348 00000642788d8ba8 1056 000000005ebe6768 00000000001661d0 6481336 Free 000000005f214d20 00000642788d8ba8 1056 000000005f215140 00000000001661d0 7346016 Free 000000005f9168a0 00000642788d8ba8 1056 000000005f916cc0 00000000001661d0 7611648 Free 00000000600591c0 00000642788d8ba8 1056 00000000600595e0 00000000001661d0 264808 Free ... Obviously I would expect this to be the case if my application were creating long-lived, large objects during each calculation. (It does do this and I accept there will be a degree of LOH fragmentation but that is not the problem here.) The problem is the very small (1056 byte) object arrays you can see in the above dump which I cannot see in code being created and which are remaining rooted somehow. Also note that CDB is not reporting the type when the heap segment is dumped: I am not sure if this is related or not. If I dump the marked (<--) object, CDB/SOS reports it fine: 0:015> !DumpObj 000000005e62fd38 Name: System.Object[] MethodTable: 00000642788d8ba8 EEClass: 00000642789d7660 Size: 1056(0x420) bytes Array: Rank 1, Number of elements 128, Type CLASS Element Type: System.Object Fields: None The elements of the object array are all strings and the strings are recognisable as from our application code. Also, I am unable to find their GC roots as the !GCRoot command hangs and never comes back (I have even tried leaving it overnight). So, I would very much appreciate it if anyone could shed any light as to why these small (<85k) object arrays are ending up on the LOH: what situations will .NET put a small object array in there? Also, does anyone happen to know of an alternative way of ascertaining the roots of these objects? Thanks in advance. Update 1 Another theory I came up with late yesterday is that these object arrays started out large but have been shrunk leaving the blocks of free memory that are evident in the memory dumps. What makes me suspicious is that the object arrays always appear to be 1056 bytes long (128 elements), 128 * 8 for the references and 32 bytes of overhead. The idea is that perhaps some unsafe code in a library or in the CLR is corrupting the number of elements field in the array header. Bit of a long shot I know... Update 2 Thanks to Brian Rasmussen (see accepted answer) the problem has been identified as fragmentation of the LOH caused by the string intern table! I wrote a quick test application to confirm this: static void Main() { const int ITERATIONS = 100000; for (int index = 0; index < ITERATIONS; ++index) { string str = "NonInterned" + index; Console.Out.WriteLine(str); } Console.Out.WriteLine("Continue."); Console.In.ReadLine(); for (int index = 0; index < ITERATIONS; ++index) { string str = string.Intern("Interned" + index); Console.Out.WriteLine(str); } Console.Out.WriteLine("Continue?"); Console.In.ReadLine(); } The application first creates and dereferences unique strings in a loop. This is just to prove that the memory does not leak in this scenario. Obviously it should not and it does not. In the second loop, unique strings are created and interned. This action roots them in the intern table. What I did not realise is how the intern table is represented. It appears it consists of a set of pages -- object arrays of 128 string elements -- that are created in the LOH. This is more evident in CDB/SOS: 0:000> .loadby sos mscorwks 0:000> !EEHeap -gc Number of GC Heaps: 1 generation 0 starts at 0x00f7a9b0 generation 1 starts at 0x00e79c3c generation 2 starts at 0x00b21000 ephemeral segment allocation context: none segment begin allocated size 00b20000 00b21000 010029bc 0x004e19bc(5118396) Large object heap starts at 0x01b21000 segment begin allocated size 01b20000 01b21000 01b8ade0 0x00069de0(433632) Total Size 0x54b79c(5552028) ------------------------------ GC Heap Size 0x54b79c(5552028) Taking a dump of the LOH segment reveals the pattern I saw in the leaking application: 0:000> !DumpHeap 01b21000 01b8ade0 ... 01b8a120 793040bc 528 01b8a330 00175e88 16 Free 01b8a340 793040bc 528 01b8a550 00175e88 16 Free 01b8a560 793040bc 528 01b8a770 00175e88 16 Free 01b8a780 793040bc 528 01b8a990 00175e88 16 Free 01b8a9a0 793040bc 528 01b8abb0 00175e88 16 Free 01b8abc0 793040bc 528 01b8add0 00175e88 16 Free total 1568 objects Statistics: MT Count TotalSize Class Name 00175e88 784 12544 Free 793040bc 784 421088 System.Object[] Total 1568 objects Note that the object array size is 528 (rather than 1056) because my workstation is 32 bit and the application server is 64 bit. The object arrays are still 128 elements long. So the moral to this story is to be very careful interning. If the string you are interning is not known to be a member of a finite set then your application will leak due to fragmentation of the LOH, at least in version 2 of the CLR. In our application's case, there is general code in the deserialisation code path that interns entity identifiers during unmarshalling: I now strongly suspect this is the culprit. However, the developer's intentions were obviously good as they wanted to make sure that if the same entity is deserialised multiple times then only one instance of the identifier string will be maintained in memory.

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  • How to use Koala Facebook Graph API?

    - by reko
    I am a Rails newbie. I want to use Koala's Graph API. In my controller @graph = Koala::Facebook::API.new('myFacebookAccessToken') @hello = @graph.get_object("my.Name") When I do this, I get something like this { "id"=>"123456", "name"=>"First Middle Last", "first_name"=>"First", "middle_name"=>"Middle", "last_name"=>"Last", "link"=>"http://www.facebook.com/MyName", "username"=>"my.name", "birthday"=>"12/12/1212", "hometown"=>{"id"=>"115200305133358163", "name"=>"City, State"}, "location"=>{"id"=>"1054648928202133335", "name"=>"City, State"}, "bio"=>"This is my awesome Bio.", "quotes"=>"I am the master of my fate; I am the captain of my soul. - William Ernest Henley\r\n\r\n"Don't go around saying the world owes you a living. The world owes you nothing. It was here first.\" - Mark Twain", "work"=>[{"employer"=>{"id"=>"100751133333", "name"=>"Company1"}, "position"=>{"id"=>"105763693332790962", "name"=>"Position1"}, "start_date"=>"2010-08", "end_date"=>"2011-07"}], "sports"=>[{"id"=>"104019549633137", "name"=>"Sport1"}, {"id"=>"103992339636529", "name"=>"Sport2"}], "favorite_teams"=>[{"id"=>"105467226133353743", "name"=>"Fav1"}, {"id"=>"19031343444432369133", "name"=>"Fav2"}, {"id"=>"98027790139333", "name"=>"Fav3"}, {"id"=>"104055132963393331", "name"=>"Fav4"}, {"id"=>"191744431437533310", "name"=>"Fav5"}], "favorite_athletes"=>[{"id"=>"10836600585799922", "name"=>"Fava1"}, {"id"=>"18995689436787722", "name"=>"Fava2"}, {"id"=>"11156342219404022", "name"=>"Fava4"}, {"id"=>"11169998212279347", "name"=>"Fava5"}, {"id"=>"122326564475039", "name"=>"Fava6"}], "inspirational_people"=>[{"id"=>"16383141733798", "name"=>"Fava7"}, {"id"=>"113529011990793335", "name"=>"fava8"}, {"id"=>"112032333138809855566", "name"=>"Fava9"}, {"id"=>"10810367588423324", "name"=>"Fava10"}], "education"=>[{"school"=>{"id"=>"13478880321332322233663", "name"=>"School1"}, "type"=>"High School", "with"=>[{"id"=>"1401052755", "name"=>"Friend1"}]}, {"school"=>{"id"=>"11482777188037224", "name"=>"School2"}, "year"=>{"id"=>"138383069535219", "name"=>"2005"}, "type"=>"High School"}, {"school"=>{"id"=>"10604484633093514", "name"=>"School3"}, "year"=>{"id"=>"142963519060927", "name"=>"2010"}, "concentration"=>[{"id"=>"10407695629335773", "name"=>"c1"}], "type"=>"College"}, {"school"=>{"id"=>"22030497466330708", "name"=>"School4"}, "degree"=>{"id"=>"19233130157477979", "name"=>"c3"}, "year"=>{"id"=>"201638419856163", "name"=>"2011"}, "type"=>"Graduate School"}], "gender"=>"male", "interested_in"=>["female"], "relationship_status"=>"Single", "religion"=>"Religion1", "political"=>"Political1", "email"=>"[email protected]", "timezone"=>-8, "locale"=>"en_US", "languages"=>[{"id"=>"10605952233759137", "name"=>"English"}, {"id"=>"10337617475934611", "name"=>"L2"}, {"id"=>"11296944428713061", "name"=>"L3"}], "verified"=>true, "updated_time"=>"2012-02-24T04:18:05+0000" } How do I show this entire hash in the view in a good format? This is what I did from what ever I learnt.. In my view <% @hello.each do |key, value| %> <li><%=h "#{key.to_s} : #{value.to_s}" %></li> <% end %> This will get the entire thing converted to a list... It works awesome if its just one key.. but how to work with multiple keys and show only the information... something like when it outputs hometown : City, State rather than something like hometown : {"id"=>"115200305133358163", "name"=>"City, State"} Also for education if I just say education[school][name] to display list of schools attended? The error i get is can't convert String into Integer I also tried to do this in my controller, but I get the same error.. @fav_teams = @hello["favorite_teams"]["name"] Also, how can I save all these to the database.. something like just the list of all schools.. not their id no's? Update: The way I plan to save to my database is.. lets say for a user model, i want to save to database as :facebook_id, :facebook_name, :facebook_firstname, ...., :facebook_hometown .. here I only want to save name... when it comes to education.. I want to save.. school, concentration and type.. I have no idea on how to achieve this.. Looking forward for help! thanks!

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  • Need help with implementing collision detection using the Separating Axis Theorem

    - by Eddie Ringle
    So, after hours of Googling and reading, I've found that the basic process of detecting a collision using SAT is: for each edge of poly A project A and B onto the normal for this edge if intervals do not overlap, return false end for for each edge of poly B project A and B onto the normal for this edge if intervals do not overlap, return false end for However, as many ways as I try to implement this in code, I just cannot get it to detect the collision. My current code is as follows: for (unsigned int i = 0; i < asteroids.size(); i++) { if (asteroids.valid(i)) { asteroids[i]->Update(); // Player-Asteroid collision detection bool collision = true; SDL_Rect asteroidBox = asteroids[i]->boundingBox; // Bullet-Asteroid collision detection for (unsigned int j = 0; j < player.bullets.size(); j++) { if (player.bullets.valid(j)) { Bullet b = player.bullets[j]; collision = true; if (b.x + (b.w / 2.0f) < asteroidBox.x - (asteroidBox.w / 2.0f)) collision = false; if (b.x - (b.w / 2.0f) > asteroidBox.x + (asteroidBox.w / 2.0f)) collision = false; if (b.y - (b.h / 2.0f) > asteroidBox.y + (asteroidBox.h / 2.0f)) collision = false; if (b.y + (b.h / 2.0f) < asteroidBox.y - (asteroidBox.h / 2.0f)) collision = false; if (collision) { bool realCollision = false; float min1, max1, min2, max2; // Create a list of vertices for the bullet CrissCross::Data::LList<Vector2D *> bullVerts; bullVerts.insert(new Vector2D(b.x - b.w / 2.0f, b.y + b.h / 2.0f)); bullVerts.insert(new Vector2D(b.x - b.w / 2.0f, b.y - b.h / 2.0f)); bullVerts.insert(new Vector2D(b.x + b.w / 2.0f, b.y - b.h / 2.0f)); bullVerts.insert(new Vector2D(b.x + b.w / 2.0f, b.y + b.h / 2.0f)); // Create a list of vectors of the edges of the bullet and the asteroid CrissCross::Data::LList<Vector2D *> bullEdges; CrissCross::Data::LList<Vector2D *> asteroidEdges; for (int k = 0; k < 4; k++) { int n = (k == 3) ? 0 : k + 1; bullEdges.insert(new Vector2D(bullVerts[k]->x - bullVerts[n]->x, bullVerts[k]->y - bullVerts[n]->y)); asteroidEdges.insert(new Vector2D(asteroids[i]->vertices[k]->x - asteroids[i]->vertices[n]->x, asteroids[i]->vertices[k]->y - asteroids[i]->vertices[n]->y)); } for (unsigned int k = 0; k < asteroidEdges.size(); k++) { Vector2D *axis = asteroidEdges[k]->getPerpendicular(); min1 = max1 = axis->dotProduct(asteroids[i]->vertices[0]); for (unsigned int l = 1; l < asteroids[i]->vertices.size(); l++) { float test = axis->dotProduct(asteroids[i]->vertices[l]); min1 = (test < min1) ? test : min1; max1 = (test > max1) ? test : max1; } min2 = max2 = axis->dotProduct(bullVerts[0]); for (unsigned int l = 1; l < bullVerts.size(); l++) { float test = axis->dotProduct(bullVerts[l]); min2 = (test < min2) ? test : min2; max2 = (test > max2) ? test : max2; } delete axis; axis = NULL; if ( (min1 - max2) > 0 || (min2 - max1) > 0 ) { realCollision = false; break; } else { realCollision = true; } } if (realCollision == false) { for (unsigned int k = 0; k < bullEdges.size(); k++) { Vector2D *axis = bullEdges[k]->getPerpendicular(); min1 = max1 = axis->dotProduct(asteroids[i]->vertices[0]); for (unsigned int l = 1; l < asteroids[i]->vertices.size(); l++) { float test = axis->dotProduct(asteroids[i]->vertices[l]); min1 = (test < min1) ? test : min1; max1 = (test > max1) ? test : max1; } min2 = max2 = axis->dotProduct(bullVerts[0]); for (unsigned int l = 1; l < bullVerts.size(); l++) { float test = axis->dotProduct(bullVerts[l]); min2 = (test < min2) ? test : min2; max2 = (test > max2) ? test : max2; } delete axis; axis = NULL; if ( (min1 - max2) > 0 || (min2 - max1) > 0 ) { realCollision = false; break; } else { realCollision = true; } } } if (realCollision) { player.bullets.remove(j); int numAsteroids; float newDegree; srand ( j + asteroidBox.x ); if ( asteroids[i]->degree == 90.0f ) { if ( rand() % 2 == 1 ) { numAsteroids = 3; newDegree = 30.0f; } else { numAsteroids = 2; newDegree = 45.0f; } for ( int k = 0; k < numAsteroids; k++) asteroids.insert(new Asteroid(asteroidBox.x + (10 * k), asteroidBox.y + (10 * k), newDegree)); } delete asteroids[i]; asteroids.remove(i); } while (bullVerts.size()) { delete bullVerts[0]; bullVerts.remove(0); } while (bullEdges.size()) { delete bullEdges[0]; bullEdges.remove(0); } while (asteroidEdges.size()) { delete asteroidEdges[0]; asteroidEdges.remove(0); } } } } } } bullEdges is a list of vectors of the edges of a bullet, asteroidEdges is similar, and bullVerts and asteroids[i].vertices are, obviously, lists of vectors of each vertex for the respective bullet or asteroid. Honestly, I'm not looking for code corrections, just a fresh set of eyes.

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  • New features of C# 4.0

    This article covers New features of C# 4.0. Article has been divided into below sections. Introduction. Dynamic Lookup. Named and Optional Arguments. Features for COM interop. Variance. Relationship with Visual Basic. Resources. Other interested readings… 22 New Features of Visual Studio 2008 for .NET Professionals 50 New Features of SQL Server 2008 IIS 7.0 New features Introduction It is now close to a year since Microsoft Visual C# 3.0 shipped as part of Visual Studio 2008. In the VS Managed Languages team we are hard at work on creating the next version of the language (with the unsurprising working title of C# 4.0), and this document is a first public description of the planned language features as we currently see them. Please be advised that all this is in early stages of production and is subject to change. Part of the reason for sharing our plans in public so early is precisely to get the kind of feedback that will cause us to improve the final product before it rolls out. Simultaneously with the publication of this whitepaper, a first public CTP (community technology preview) of Visual Studio 2010 is going out as a Virtual PC image for everyone to try. Please use it to play and experiment with the features, and let us know of any thoughts you have. We ask for your understanding and patience working with very early bits, where especially new or newly implemented features do not have the quality or stability of a final product. The aim of the CTP is not to give you a productive work environment but to give you the best possible impression of what we are working on for the next release. The CTP contains a number of walkthroughs, some of which highlight the new language features of C# 4.0. Those are excellent for getting a hands-on guided tour through the details of some common scenarios for the features. You may consider this whitepaper a companion document to these walkthroughs, complementing them with a focus on the overall language features and how they work, as opposed to the specifics of the concrete scenarios. C# 4.0 The major theme for C# 4.0 is dynamic programming. Increasingly, objects are “dynamic” in the sense that their structure and behavior is not captured by a static type, or at least not one that the compiler knows about when compiling your program. Some examples include a. objects from dynamic programming languages, such as Python or Ruby b. COM objects accessed through IDispatch c. ordinary .NET types accessed through reflection d. objects with changing structure, such as HTML DOM objects While C# remains a statically typed language, we aim to vastly improve the interaction with such objects. A secondary theme is co-evolution with Visual Basic. Going forward we will aim to maintain the individual character of each language, but at the same time important new features should be introduced in both languages at the same time. They should be differentiated more by style and feel than by feature set. The new features in C# 4.0 fall into four groups: Dynamic lookup Dynamic lookup allows you to write method, operator and indexer calls, property and field accesses, and even object invocations which bypass the C# static type checking and instead gets resolved at runtime. Named and optional parameters Parameters in C# can now be specified as optional by providing a default value for them in a member declaration. When the member is invoked, optional arguments can be omitted. Furthermore, any argument can be passed by parameter name instead of position. COM specific interop features Dynamic lookup as well as named and optional parameters both help making programming against COM less painful than today. On top of that, however, we are adding a number of other small features that further improve the interop experience. Variance It used to be that an IEnumerable<string> wasn’t an IEnumerable<object>. Now it is – C# embraces type safe “co-and contravariance” and common BCL types are updated to take advantage of that. Dynamic Lookup Dynamic lookup allows you a unified approach to invoking things dynamically. With dynamic lookup, when you have an object in your hand you do not need to worry about whether it comes from COM, IronPython, the HTML DOM or reflection; you just apply operations to it and leave it to the runtime to figure out what exactly those operations mean for that particular object. This affords you enormous flexibility, and can greatly simplify your code, but it does come with a significant drawback: Static typing is not maintained for these operations. A dynamic object is assumed at compile time to support any operation, and only at runtime will you get an error if it wasn’t so. Oftentimes this will be no loss, because the object wouldn’t have a static type anyway, in other cases it is a tradeoff between brevity and safety. In order to facilitate this tradeoff, it is a design goal of C# to allow you to opt in or opt out of dynamic behavior on every single call. The dynamic type C# 4.0 introduces a new static type called dynamic. When you have an object of type dynamic you can “do things to it” that are resolved only at runtime: dynamic d = GetDynamicObject(…); d.M(7); The C# compiler allows you to call a method with any name and any arguments on d because it is of type dynamic. At runtime the actual object that d refers to will be examined to determine what it means to “call M with an int” on it. The type dynamic can be thought of as a special version of the type object, which signals that the object can be used dynamically. It is easy to opt in or out of dynamic behavior: any object can be implicitly converted to dynamic, “suspending belief” until runtime. Conversely, there is an “assignment conversion” from dynamic to any other type, which allows implicit conversion in assignment-like constructs: dynamic d = 7; // implicit conversion int i = d; // assignment conversion Dynamic operations Not only method calls, but also field and property accesses, indexer and operator calls and even delegate invocations can be dispatched dynamically: dynamic d = GetDynamicObject(…); d.M(7); // calling methods d.f = d.P; // getting and settings fields and properties d[“one”] = d[“two”]; // getting and setting thorugh indexers int i = d + 3; // calling operators string s = d(5,7); // invoking as a delegate The role of the C# compiler here is simply to package up the necessary information about “what is being done to d”, so that the runtime can pick it up and determine what the exact meaning of it is given an actual object d. Think of it as deferring part of the compiler’s job to runtime. The result of any dynamic operation is itself of type dynamic. Runtime lookup At runtime a dynamic operation is dispatched according to the nature of its target object d: COM objects If d is a COM object, the operation is dispatched dynamically through COM IDispatch. This allows calling to COM types that don’t have a Primary Interop Assembly (PIA), and relying on COM features that don’t have a counterpart in C#, such as indexed properties and default properties. Dynamic objects If d implements the interface IDynamicObject d itself is asked to perform the operation. Thus by implementing IDynamicObject a type can completely redefine the meaning of dynamic operations. This is used intensively by dynamic languages such as IronPython and IronRuby to implement their own dynamic object models. It will also be used by APIs, e.g. by the HTML DOM to allow direct access to the object’s properties using property syntax. Plain objects Otherwise d is a standard .NET object, and the operation will be dispatched using reflection on its type and a C# “runtime binder” which implements C#’s lookup and overload resolution semantics at runtime. This is essentially a part of the C# compiler running as a runtime component to “finish the work” on dynamic operations that was deferred by the static compiler. Example Assume the following code: dynamic d1 = new Foo(); dynamic d2 = new Bar(); string s; d1.M(s, d2, 3, null); Because the receiver of the call to M is dynamic, the C# compiler does not try to resolve the meaning of the call. Instead it stashes away information for the runtime about the call. This information (often referred to as the “payload”) is essentially equivalent to: “Perform an instance method call of M with the following arguments: 1. a string 2. a dynamic 3. a literal int 3 4. a literal object null” At runtime, assume that the actual type Foo of d1 is not a COM type and does not implement IDynamicObject. In this case the C# runtime binder picks up to finish the overload resolution job based on runtime type information, proceeding as follows: 1. Reflection is used to obtain the actual runtime types of the two objects, d1 and d2, that did not have a static type (or rather had the static type dynamic). The result is Foo for d1 and Bar for d2. 2. Method lookup and overload resolution is performed on the type Foo with the call M(string,Bar,3,null) using ordinary C# semantics. 3. If the method is found it is invoked; otherwise a runtime exception is thrown. Overload resolution with dynamic arguments Even if the receiver of a method call is of a static type, overload resolution can still happen at runtime. This can happen if one or more of the arguments have the type dynamic: Foo foo = new Foo(); dynamic d = new Bar(); var result = foo.M(d); The C# runtime binder will choose between the statically known overloads of M on Foo, based on the runtime type of d, namely Bar. The result is again of type dynamic. The Dynamic Language Runtime An important component in the underlying implementation of dynamic lookup is the Dynamic Language Runtime (DLR), which is a new API in .NET 4.0. The DLR provides most of the infrastructure behind not only C# dynamic lookup but also the implementation of several dynamic programming languages on .NET, such as IronPython and IronRuby. Through this common infrastructure a high degree of interoperability is ensured, but just as importantly the DLR provides excellent caching mechanisms which serve to greatly enhance the efficiency of runtime dispatch. To the user of dynamic lookup in C#, the DLR is invisible except for the improved efficiency. However, if you want to implement your own dynamically dispatched objects, the IDynamicObject interface allows you to interoperate with the DLR and plug in your own behavior. This is a rather advanced task, which requires you to understand a good deal more about the inner workings of the DLR. For API writers, however, it can definitely be worth the trouble in order to vastly improve the usability of e.g. a library representing an inherently dynamic domain. Open issues There are a few limitations and things that might work differently than you would expect. · The DLR allows objects to be created from objects that represent classes. However, the current implementation of C# doesn’t have syntax to support this. · Dynamic lookup will not be able to find extension methods. Whether extension methods apply or not depends on the static context of the call (i.e. which using clauses occur), and this context information is not currently kept as part of the payload. · Anonymous functions (i.e. lambda expressions) cannot appear as arguments to a dynamic method call. The compiler cannot bind (i.e. “understand”) an anonymous function without knowing what type it is converted to. One consequence of these limitations is that you cannot easily use LINQ queries over dynamic objects: dynamic collection = …; var result = collection.Select(e => e + 5); If the Select method is an extension method, dynamic lookup will not find it. Even if it is an instance method, the above does not compile, because a lambda expression cannot be passed as an argument to a dynamic operation. There are no plans to address these limitations in C# 4.0. Named and Optional Arguments Named and optional parameters are really two distinct features, but are often useful together. Optional parameters allow you to omit arguments to member invocations, whereas named arguments is a way to provide an argument using the name of the corresponding parameter instead of relying on its position in the parameter list. Some APIs, most notably COM interfaces such as the Office automation APIs, are written specifically with named and optional parameters in mind. Up until now it has been very painful to call into these APIs from C#, with sometimes as many as thirty arguments having to be explicitly passed, most of which have reasonable default values and could be omitted. Even in APIs for .NET however you sometimes find yourself compelled to write many overloads of a method with different combinations of parameters, in order to provide maximum usability to the callers. Optional parameters are a useful alternative for these situations. Optional parameters A parameter is declared optional simply by providing a default value for it: public void M(int x, int y = 5, int z = 7); Here y and z are optional parameters and can be omitted in calls: M(1, 2, 3); // ordinary call of M M(1, 2); // omitting z – equivalent to M(1, 2, 7) M(1); // omitting both y and z – equivalent to M(1, 5, 7) Named and optional arguments C# 4.0 does not permit you to omit arguments between commas as in M(1,,3). This could lead to highly unreadable comma-counting code. Instead any argument can be passed by name. Thus if you want to omit only y from a call of M you can write: M(1, z: 3); // passing z by name or M(x: 1, z: 3); // passing both x and z by name or even M(z: 3, x: 1); // reversing the order of arguments All forms are equivalent, except that arguments are always evaluated in the order they appear, so in the last example the 3 is evaluated before the 1. Optional and named arguments can be used not only with methods but also with indexers and constructors. Overload resolution Named and optional arguments affect overload resolution, but the changes are relatively simple: A signature is applicable if all its parameters are either optional or have exactly one corresponding argument (by name or position) in the call which is convertible to the parameter type. Betterness rules on conversions are only applied for arguments that are explicitly given – omitted optional arguments are ignored for betterness purposes. If two signatures are equally good, one that does not omit optional parameters is preferred. M(string s, int i = 1); M(object o); M(int i, string s = “Hello”); M(int i); M(5); Given these overloads, we can see the working of the rules above. M(string,int) is not applicable because 5 doesn’t convert to string. M(int,string) is applicable because its second parameter is optional, and so, obviously are M(object) and M(int). M(int,string) and M(int) are both better than M(object) because the conversion from 5 to int is better than the conversion from 5 to object. Finally M(int) is better than M(int,string) because no optional arguments are omitted. Thus the method that gets called is M(int). Features for COM interop Dynamic lookup as well as named and optional parameters greatly improve the experience of interoperating with COM APIs such as the Office Automation APIs. In order to remove even more of the speed bumps, a couple of small COM-specific features are also added to C# 4.0. Dynamic import Many COM methods accept and return variant types, which are represented in the PIAs as object. In the vast majority of cases, a programmer calling these methods already knows the static type of a returned object from context, but explicitly has to perform a cast on the returned value to make use of that knowledge. These casts are so common that they constitute a major nuisance. In order to facilitate a smoother experience, you can now choose to import these COM APIs in such a way that variants are instead represented using the type dynamic. In other words, from your point of view, COM signatures now have occurrences of dynamic instead of object in them. This means that you can easily access members directly off a returned object, or you can assign it to a strongly typed local variable without having to cast. To illustrate, you can now say excel.Cells[1, 1].Value = "Hello"; instead of ((Excel.Range)excel.Cells[1, 1]).Value2 = "Hello"; and Excel.Range range = excel.Cells[1, 1]; instead of Excel.Range range = (Excel.Range)excel.Cells[1, 1]; Compiling without PIAs Primary Interop Assemblies are large .NET assemblies generated from COM interfaces to facilitate strongly typed interoperability. They provide great support at design time, where your experience of the interop is as good as if the types where really defined in .NET. However, at runtime these large assemblies can easily bloat your program, and also cause versioning issues because they are distributed independently of your application. The no-PIA feature allows you to continue to use PIAs at design time without having them around at runtime. Instead, the C# compiler will bake the small part of the PIA that a program actually uses directly into its assembly. At runtime the PIA does not have to be loaded. Omitting ref Because of a different programming model, many COM APIs contain a lot of reference parameters. Contrary to refs in C#, these are typically not meant to mutate a passed-in argument for the subsequent benefit of the caller, but are simply another way of passing value parameters. It therefore seems unreasonable that a C# programmer should have to create temporary variables for all such ref parameters and pass these by reference. Instead, specifically for COM methods, the C# compiler will allow you to pass arguments by value to such a method, and will automatically generate temporary variables to hold the passed-in values, subsequently discarding these when the call returns. In this way the caller sees value semantics, and will not experience any side effects, but the called method still gets a reference. Open issues A few COM interface features still are not surfaced in C#. Most notably these include indexed properties and default properties. As mentioned above these will be respected if you access COM dynamically, but statically typed C# code will still not recognize them. There are currently no plans to address these remaining speed bumps in C# 4.0. Variance An aspect of generics that often comes across as surprising is that the following is illegal: IList<string> strings = new List<string>(); IList<object> objects = strings; The second assignment is disallowed because strings does not have the same element type as objects. There is a perfectly good reason for this. If it were allowed you could write: objects[0] = 5; string s = strings[0]; Allowing an int to be inserted into a list of strings and subsequently extracted as a string. This would be a breach of type safety. However, there are certain interfaces where the above cannot occur, notably where there is no way to insert an object into the collection. Such an interface is IEnumerable<T>. If instead you say: IEnumerable<object> objects = strings; There is no way we can put the wrong kind of thing into strings through objects, because objects doesn’t have a method that takes an element in. Variance is about allowing assignments such as this in cases where it is safe. The result is that a lot of situations that were previously surprising now just work. Covariance In .NET 4.0 the IEnumerable<T> interface will be declared in the following way: public interface IEnumerable<out T> : IEnumerable { IEnumerator<T> GetEnumerator(); } public interface IEnumerator<out T> : IEnumerator { bool MoveNext(); T Current { get; } } The “out” in these declarations signifies that the T can only occur in output position in the interface – the compiler will complain otherwise. In return for this restriction, the interface becomes “covariant” in T, which means that an IEnumerable<A> is considered an IEnumerable<B> if A has a reference conversion to B. As a result, any sequence of strings is also e.g. a sequence of objects. This is useful e.g. in many LINQ methods. Using the declarations above: var result = strings.Union(objects); // succeeds with an IEnumerable<object> This would previously have been disallowed, and you would have had to to some cumbersome wrapping to get the two sequences to have the same element type. Contravariance Type parameters can also have an “in” modifier, restricting them to occur only in input positions. An example is IComparer<T>: public interface IComparer<in T> { public int Compare(T left, T right); } The somewhat baffling result is that an IComparer<object> can in fact be considered an IComparer<string>! It makes sense when you think about it: If a comparer can compare any two objects, it can certainly also compare two strings. This property is referred to as contravariance. A generic type can have both in and out modifiers on its type parameters, as is the case with the Func<…> delegate types: public delegate TResult Func<in TArg, out TResult>(TArg arg); Obviously the argument only ever comes in, and the result only ever comes out. Therefore a Func<object,string> can in fact be used as a Func<string,object>. Limitations Variant type parameters can only be declared on interfaces and delegate types, due to a restriction in the CLR. Variance only applies when there is a reference conversion between the type arguments. For instance, an IEnumerable<int> is not an IEnumerable<object> because the conversion from int to object is a boxing conversion, not a reference conversion. Also please note that the CTP does not contain the new versions of the .NET types mentioned above. In order to experiment with variance you have to declare your own variant interfaces and delegate types. COM Example Here is a larger Office automation example that shows many of the new C# features in action. using System; using System.Diagnostics; using System.Linq; using Excel = Microsoft.Office.Interop.Excel; using Word = Microsoft.Office.Interop.Word; class Program { static void Main(string[] args) { var excel = new Excel.Application(); excel.Visible = true; excel.Workbooks.Add(); // optional arguments omitted excel.Cells[1, 1].Value = "Process Name"; // no casts; Value dynamically excel.Cells[1, 2].Value = "Memory Usage"; // accessed var processes = Process.GetProcesses() .OrderByDescending(p =&gt; p.WorkingSet) .Take(10); int i = 2; foreach (var p in processes) { excel.Cells[i, 1].Value = p.ProcessName; // no casts excel.Cells[i, 2].Value = p.WorkingSet; // no casts i++; } Excel.Range range = excel.Cells[1, 1]; // no casts Excel.Chart chart = excel.ActiveWorkbook.Charts. Add(After: excel.ActiveSheet); // named and optional arguments chart.ChartWizard( Source: range.CurrentRegion, Title: "Memory Usage in " + Environment.MachineName); //named+optional chart.ChartStyle = 45; chart.CopyPicture(Excel.XlPictureAppearance.xlScreen, Excel.XlCopyPictureFormat.xlBitmap, Excel.XlPictureAppearance.xlScreen); var word = new Word.Application(); word.Visible = true; word.Documents.Add(); // optional arguments word.Selection.Paste(); } } The code is much more terse and readable than the C# 3.0 counterpart. Note especially how the Value property is accessed dynamically. This is actually an indexed property, i.e. a property that takes an argument; something which C# does not understand. However the argument is optional. Since the access is dynamic, it goes through the runtime COM binder which knows to substitute the default value and call the indexed property. Thus, dynamic COM allows you to avoid accesses to the puzzling Value2 property of Excel ranges. Relationship with Visual Basic A number of the features introduced to C# 4.0 already exist or will be introduced in some form or other in Visual Basic: · Late binding in VB is similar in many ways to dynamic lookup in C#, and can be expected to make more use of the DLR in the future, leading to further parity with C#. · Named and optional arguments have been part of Visual Basic for a long time, and the C# version of the feature is explicitly engineered with maximal VB interoperability in mind. · NoPIA and variance are both being introduced to VB and C# at the same time. VB in turn is adding a number of features that have hitherto been a mainstay of C#. As a result future versions of C# and VB will have much better feature parity, for the benefit of everyone. Resources All available resources concerning C# 4.0 can be accessed through the C# Dev Center. Specifically, this white paper and other resources can be found at the Code Gallery site. Enjoy! span.fullpost {display:none;}

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  • LSI 9285-8e and Supermicro SC837E26-RJBOD1 duplicate enclosure ID and slot numbers

    - by Andy Shinn
    I am working with 2 x Supermicro SC837E26-RJBOD1 chassis connected to a single LSI 9285-8e card in a Supermicro 1U host. There are 28 drives in each chassis for a total of 56 drives in 28 RAID1 mirrors. The problem I am running in to is that there are duplicate slots for the 2 chassis (the slots list twice and only go from 0 to 27). All the drives also show the same enclosure ID (ID 36). However, MegaCLI -encinfo lists the 2 enclosures correctly (ID 36 and ID 65). My question is, why would this happen? Is there an option I am missing to use 2 enclosures effectively? This is blocking me rebuilding a drive that failed in slot 11 since I can only specify enclosure and slot as parameters to replace a drive. When I do this, it picks the wrong slot 11 (device ID 46 instead of device ID 19). Adapter #1 is the LSI 9285-8e, adapter #0 (which I removed due to space limitations) is the onboard LSI. Adapter information: Adapter #1 ============================================================================== Versions ================ Product Name : LSI MegaRAID SAS 9285-8e Serial No : SV12704804 FW Package Build: 23.1.1-0004 Mfg. Data ================ Mfg. Date : 06/30/11 Rework Date : 00/00/00 Revision No : 00A Battery FRU : N/A Image Versions in Flash: ================ BIOS Version : 5.25.00_4.11.05.00_0x05040000 WebBIOS Version : 6.1-20-e_20-Rel Preboot CLI Version: 05.01-04:#%00001 FW Version : 3.140.15-1320 NVDATA Version : 2.1106.03-0051 Boot Block Version : 2.04.00.00-0001 BOOT Version : 06.253.57.219 Pending Images in Flash ================ None PCI Info ================ Vendor Id : 1000 Device Id : 005b SubVendorId : 1000 SubDeviceId : 9285 Host Interface : PCIE ChipRevision : B0 Number of Frontend Port: 0 Device Interface : PCIE Number of Backend Port: 8 Port : Address 0 5003048000ee8e7f 1 5003048000ee8a7f 2 0000000000000000 3 0000000000000000 4 0000000000000000 5 0000000000000000 6 0000000000000000 7 0000000000000000 HW Configuration ================ SAS Address : 500605b0038f9210 BBU : Present Alarm : Present NVRAM : Present Serial Debugger : Present Memory : Present Flash : Present Memory Size : 1024MB TPM : Absent On board Expander: Absent Upgrade Key : Absent Temperature sensor for ROC : Present Temperature sensor for controller : Absent ROC temperature : 70 degree Celcius Settings ================ Current Time : 18:24:36 3/13, 2012 Predictive Fail Poll Interval : 300sec Interrupt Throttle Active Count : 16 Interrupt Throttle Completion : 50us Rebuild Rate : 30% PR Rate : 30% BGI Rate : 30% Check Consistency Rate : 30% Reconstruction Rate : 30% Cache Flush Interval : 4s Max Drives to Spinup at One Time : 2 Delay Among Spinup Groups : 12s Physical Drive Coercion Mode : Disabled Cluster Mode : Disabled Alarm : Enabled Auto Rebuild : Enabled Battery Warning : Enabled Ecc Bucket Size : 15 Ecc Bucket Leak Rate : 1440 Minutes Restore HotSpare on Insertion : Disabled Expose Enclosure Devices : Enabled Maintain PD Fail History : Enabled Host Request Reordering : Enabled Auto Detect BackPlane Enabled : SGPIO/i2c SEP Load Balance Mode : Auto Use FDE Only : No Security Key Assigned : No Security Key Failed : No Security Key Not Backedup : No Default LD PowerSave Policy : Controller Defined Maximum number of direct attached drives to spin up in 1 min : 10 Any Offline VD Cache Preserved : No Allow Boot with Preserved Cache : No Disable Online Controller Reset : No PFK in NVRAM : No Use disk activity for locate : No Capabilities ================ RAID Level Supported : RAID0, RAID1, RAID5, RAID6, RAID00, RAID10, RAID50, RAID60, PRL 11, PRL 11 with spanning, SRL 3 supported, PRL11-RLQ0 DDF layout with no span, PRL11-RLQ0 DDF layout with span Supported Drives : SAS, SATA Allowed Mixing: Mix in Enclosure Allowed Mix of SAS/SATA of HDD type in VD Allowed Status ================ ECC Bucket Count : 0 Limitations ================ Max Arms Per VD : 32 Max Spans Per VD : 8 Max Arrays : 128 Max Number of VDs : 64 Max Parallel Commands : 1008 Max SGE Count : 60 Max Data Transfer Size : 8192 sectors Max Strips PerIO : 42 Max LD per array : 16 Min Strip Size : 8 KB Max Strip Size : 1.0 MB Max Configurable CacheCade Size: 0 GB Current Size of CacheCade : 0 GB Current Size of FW Cache : 887 MB Device Present ================ Virtual Drives : 28 Degraded : 0 Offline : 0 Physical Devices : 59 Disks : 56 Critical Disks : 0 Failed Disks : 0 Supported Adapter Operations ================ Rebuild Rate : Yes CC Rate : Yes BGI Rate : Yes Reconstruct Rate : Yes Patrol Read Rate : Yes Alarm Control : Yes Cluster Support : No BBU : No Spanning : Yes Dedicated Hot Spare : Yes Revertible Hot Spares : Yes Foreign Config Import : Yes Self Diagnostic : Yes Allow Mixed Redundancy on Array : No Global Hot Spares : Yes Deny SCSI Passthrough : No Deny SMP Passthrough : No Deny STP Passthrough : No Support Security : No Snapshot Enabled : No Support the OCE without adding drives : Yes Support PFK : Yes Support PI : No Support Boot Time PFK Change : Yes Disable Online PFK Change : No PFK TrailTime Remaining : 0 days 0 hours Support Shield State : Yes Block SSD Write Disk Cache Change: Yes Supported VD Operations ================ Read Policy : Yes Write Policy : Yes IO Policy : Yes Access Policy : Yes Disk Cache Policy : Yes Reconstruction : Yes Deny Locate : No Deny CC : No Allow Ctrl Encryption: No Enable LDBBM : No Support Breakmirror : No Power Savings : Yes Supported PD Operations ================ Force Online : Yes Force Offline : Yes Force Rebuild : Yes Deny Force Failed : No Deny Force Good/Bad : No Deny Missing Replace : No Deny Clear : No Deny Locate : No Support Temperature : Yes Disable Copyback : No Enable JBOD : No Enable Copyback on SMART : No Enable Copyback to SSD on SMART Error : Yes Enable SSD Patrol Read : No PR Correct Unconfigured Areas : Yes Enable Spin Down of UnConfigured Drives : Yes Disable Spin Down of hot spares : No Spin Down time : 30 T10 Power State : Yes Error Counters ================ Memory Correctable Errors : 0 Memory Uncorrectable Errors : 0 Cluster Information ================ Cluster Permitted : No Cluster Active : No Default Settings ================ Phy Polarity : 0 Phy PolaritySplit : 0 Background Rate : 30 Strip Size : 64kB Flush Time : 4 seconds Write Policy : WB Read Policy : Adaptive Cache When BBU Bad : Disabled Cached IO : No SMART Mode : Mode 6 Alarm Disable : Yes Coercion Mode : None ZCR Config : Unknown Dirty LED Shows Drive Activity : No BIOS Continue on Error : No Spin Down Mode : None Allowed Device Type : SAS/SATA Mix Allow Mix in Enclosure : Yes Allow HDD SAS/SATA Mix in VD : Yes Allow SSD SAS/SATA Mix in VD : No Allow HDD/SSD Mix in VD : No Allow SATA in Cluster : No Max Chained Enclosures : 16 Disable Ctrl-R : Yes Enable Web BIOS : Yes Direct PD Mapping : No BIOS Enumerate VDs : Yes Restore Hot Spare on Insertion : No Expose Enclosure Devices : Yes Maintain PD Fail History : Yes Disable Puncturing : No Zero Based Enclosure Enumeration : No PreBoot CLI Enabled : Yes LED Show Drive Activity : Yes Cluster Disable : Yes SAS Disable : No Auto Detect BackPlane Enable : SGPIO/i2c SEP Use FDE Only : No Enable Led Header : No Delay during POST : 0 EnableCrashDump : No Disable Online Controller Reset : No EnableLDBBM : No Un-Certified Hard Disk Drives : Allow Treat Single span R1E as R10 : No Max LD per array : 16 Power Saving option : Don't Auto spin down Configured Drives Max power savings option is not allowed for LDs. Only T10 power conditions are to be used. Default spin down time in minutes: 30 Enable JBOD : No TTY Log In Flash : No Auto Enhanced Import : No BreakMirror RAID Support : No Disable Join Mirror : No Enable Shield State : Yes Time taken to detect CME : 60s Exit Code: 0x00 Enclosure information: # /opt/MegaRAID/MegaCli/MegaCli64 -encinfo -a1 Number of enclosures on adapter 1 -- 3 Enclosure 0: Device ID : 36 Number of Slots : 28 Number of Power Supplies : 2 Number of Fans : 3 Number of Temperature Sensors : 1 Number of Alarms : 1 Number of SIM Modules : 0 Number of Physical Drives : 28 Status : Normal Position : 1 Connector Name : Port B Enclosure type : SES VendorId is LSI CORP and Product Id is SAS2X36 VendorID and Product ID didnt match FRU Part Number : N/A Enclosure Serial Number : N/A ESM Serial Number : N/A Enclosure Zoning Mode : N/A Partner Device Id : 65 Inquiry data : Vendor Identification : LSI CORP Product Identification : SAS2X36 Product Revision Level : 0718 Vendor Specific : x36-55.7.24.1 Number of Voltage Sensors :2 Voltage Sensor :0 Voltage Sensor Status :OK Voltage Value :5020 milli volts Voltage Sensor :1 Voltage Sensor Status :OK Voltage Value :11820 milli volts Number of Power Supplies : 2 Power Supply : 0 Power Supply Status : OK Power Supply : 1 Power Supply Status : OK Number of Fans : 3 Fan : 0 Fan Speed :Low Speed Fan Status : OK Fan : 1 Fan Speed :Low Speed Fan Status : OK Fan : 2 Fan Speed :Low Speed Fan Status : OK Number of Temperature Sensors : 1 Temp Sensor : 0 Temperature : 48 Temperature Sensor Status : OK Number of Chassis : 1 Chassis : 0 Chassis Status : OK Enclosure 1: Device ID : 65 Number of Slots : 28 Number of Power Supplies : 2 Number of Fans : 3 Number of Temperature Sensors : 1 Number of Alarms : 1 Number of SIM Modules : 0 Number of Physical Drives : 28 Status : Normal Position : 1 Connector Name : Port A Enclosure type : SES VendorId is LSI CORP and Product Id is SAS2X36 VendorID and Product ID didnt match FRU Part Number : N/A Enclosure Serial Number : N/A ESM Serial Number : N/A Enclosure Zoning Mode : N/A Partner Device Id : 36 Inquiry data : Vendor Identification : LSI CORP Product Identification : SAS2X36 Product Revision Level : 0718 Vendor Specific : x36-55.7.24.1 Number of Voltage Sensors :2 Voltage Sensor :0 Voltage Sensor Status :OK Voltage Value :5020 milli volts Voltage Sensor :1 Voltage Sensor Status :OK Voltage Value :11760 milli volts Number of Power Supplies : 2 Power Supply : 0 Power Supply Status : OK Power Supply : 1 Power Supply Status : OK Number of Fans : 3 Fan : 0 Fan Speed :Low Speed Fan Status : OK Fan : 1 Fan Speed :Low Speed Fan Status : OK Fan : 2 Fan Speed :Low Speed Fan Status : OK Number of Temperature Sensors : 1 Temp Sensor : 0 Temperature : 47 Temperature Sensor Status : OK Number of Chassis : 1 Chassis : 0 Chassis Status : OK Enclosure 2: Device ID : 252 Number of Slots : 8 Number of Power Supplies : 0 Number of Fans : 0 Number of Temperature Sensors : 0 Number of Alarms : 0 Number of SIM Modules : 1 Number of Physical Drives : 0 Status : Normal Position : 1 Connector Name : Unavailable Enclosure type : SGPIO Failed in first Inquiry commnad FRU Part Number : N/A Enclosure Serial Number : N/A ESM Serial Number : N/A Enclosure Zoning Mode : N/A Partner Device Id : Unavailable Inquiry data : Vendor Identification : LSI Product Identification : SGPIO Product Revision Level : N/A Vendor Specific : Exit Code: 0x00 Now, notice that each slot 11 device shows an enclosure ID of 36, I think this is where the discrepancy happens. One should be 36. But the other should be on enclosure 65. Drives in slot 11: Enclosure Device ID: 36 Slot Number: 11 Drive's postion: DiskGroup: 5, Span: 0, Arm: 1 Enclosure position: 0 Device Id: 48 WWN: Sequence Number: 11 Media Error Count: 0 Other Error Count: 0 Predictive Failure Count: 0 Last Predictive Failure Event Seq Number: 0 PD Type: SATA Raw Size: 2.728 TB [0x15d50a3b0 Sectors] Non Coerced Size: 2.728 TB [0x15d40a3b0 Sectors] Coerced Size: 2.728 TB [0x15d400000 Sectors] Firmware state: Online, Spun Up Is Commissioned Spare : YES Device Firmware Level: A5C0 Shield Counter: 0 Successful diagnostics completion on : N/A SAS Address(0): 0x5003048000ee8a53 Connected Port Number: 1(path0) Inquiry Data: MJ1311YNG6YYXAHitachi HDS5C3030ALA630 MEAOA5C0 FDE Enable: Disable Secured: Unsecured Locked: Unlocked Needs EKM Attention: No Foreign State: None Device Speed: 6.0Gb/s Link Speed: 6.0Gb/s Media Type: Hard Disk Device Drive Temperature :30C (86.00 F) PI Eligibility: No Drive is formatted for PI information: No PI: No PI Drive's write cache : Disabled Drive's NCQ setting : Enabled Port-0 : Port status: Active Port's Linkspeed: 6.0Gb/s Drive has flagged a S.M.A.R.T alert : No Enclosure Device ID: 36 Slot Number: 11 Drive's postion: DiskGroup: 19, Span: 0, Arm: 1 Enclosure position: 0 Device Id: 19 WWN: Sequence Number: 4 Media Error Count: 0 Other Error Count: 0 Predictive Failure Count: 0 Last Predictive Failure Event Seq Number: 0 PD Type: SATA Raw Size: 2.728 TB [0x15d50a3b0 Sectors] Non Coerced Size: 2.728 TB [0x15d40a3b0 Sectors] Coerced Size: 2.728 TB [0x15d400000 Sectors] Firmware state: Online, Spun Up Is Commissioned Spare : NO Device Firmware Level: A580 Shield Counter: 0 Successful diagnostics completion on : N/A SAS Address(0): 0x5003048000ee8e53 Connected Port Number: 0(path0) Inquiry Data: MJ1313YNG1VA5CHitachi HDS5C3030ALA630 MEAOA580 FDE Enable: Disable Secured: Unsecured Locked: Unlocked Needs EKM Attention: No Foreign State: None Device Speed: 6.0Gb/s Link Speed: 6.0Gb/s Media Type: Hard Disk Device Drive Temperature :30C (86.00 F) PI Eligibility: No Drive is formatted for PI information: No PI: No PI Drive's write cache : Disabled Drive's NCQ setting : Enabled Port-0 : Port status: Active Port's Linkspeed: 6.0Gb/s Drive has flagged a S.M.A.R.T alert : No Update 06/28/12: I finally have some new information about (what we think) the root cause of this problem so I thought I would share. After getting in contact with a very knowledgeable Supermicro tech, they provided us with a tool called Xflash (doesn't appear to be readily available on their FTP). When we gathered some information using this utility, my colleague found something very strange: root@mogile2 test]# ./xflash.dat -i get avail Initializing Interface. Expander: SAS2X36 (SAS2x36) 1) SAS2X36 (SAS2x36) (50030480:00EE917F) (0.0.0.0) 2) SAS2X36 (SAS2x36) (50030480:00E9D67F) (0.0.0.0) 3) SAS2X36 (SAS2x36) (50030480:0112D97F) (0.0.0.0) This lists the connected enclosures. You see the 3 connected (we have since added a 3rd and a 4th which is not yet showing up) with their respective SAS address / WWN (50030480:00EE917F). Now we can use this address to get information on the individual enclosures: [root@mogile2 test]# ./xflash.dat -i 5003048000EE917F get exp Initializing Interface. Expander: SAS2X36 (SAS2x36) Reading the expander information.......... Expander: SAS2X36 (SAS2x36) B3 SAS Address: 50030480:00EE917F Enclosure Logical Id: 50030480:0000007F IP Address: 0.0.0.0 Component Identifier: 0x0223 Component Revision: 0x05 [root@mogile2 test]# ./xflash.dat -i 5003048000E9D67F get exp Initializing Interface. Expander: SAS2X36 (SAS2x36) Reading the expander information.......... Expander: SAS2X36 (SAS2x36) B3 SAS Address: 50030480:00E9D67F Enclosure Logical Id: 50030480:0000007F IP Address: 0.0.0.0 Component Identifier: 0x0223 Component Revision: 0x05 [root@mogile2 test]# ./xflash.dat -i 500304800112D97F get exp Initializing Interface. Expander: SAS2X36 (SAS2x36) Reading the expander information.......... Expander: SAS2X36 (SAS2x36) B3 SAS Address: 50030480:0112D97F Enclosure Logical Id: 50030480:0112D97F IP Address: 0.0.0.0 Component Identifier: 0x0223 Component Revision: 0x05 Did you catch it? The first 2 enclosures logical ID is partially masked out where the 3rd one (which has a correct unique enclosure ID) is not. We pointed this out to Supermicro and were able to confirm that this address is supposed to be set during manufacturing and there was a problem with a certain batch of these enclosures where the logical ID was not set. We believe that the RAID controller is determining the ID based on the logical ID and since our first 2 enclosures have the same logical ID, they get the same enclosure ID. We also confirmed that 0000007F is the default which comes from LSI as an ID. The next pointer that helps confirm this could be a manufacturing problem with a run of JBODs is the fact that all 6 of the enclosures that have this problem begin with 00E. I believe that between 00E8 and 00EE Supermicro forgot to program the logical IDs correctly and neglected to recall or fix the problem post production. Fortunately for us, there is a tool to manage the WWN and logical ID of the devices from Supermicro: ftp://ftp.supermicro.com/utility/ExpanderXtools_Lite/. Our next step is to schedule a shutdown of these JBODs (after data migration) and reprogram the logical ID and see if it solves the problem. Update 06/28/12 #2: I just discovered this FAQ at Supermicro while Google searching for "lsi 0000007f": http://www.supermicro.com/support/faqs/faq.cfm?faq=11805. I still don't understand why, in the last several times we contacted Supermicro, they would have never directed us to this article :\

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