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• VirtualBox 3.2 is released! A Red Letter Day?

  - by Fat Bloke

  Big news today! A new release of VirtualBox packed full of innovation and improvements. Over the next few weeks we'll take a closer look at some of these new features in a lot more depth, but today we'll whet your appetite with the headline descriptions. To start with, we should point out that this is the first Oracle-branded version which makes today a real Red-letter day ;-)  Oracle VM VirtualBox 3.2 Version 3.2 moves VirtualBox forward in 3 main areas ( handily, all beginning with "P" ) : performance, power and supported guest operating system platforms.  Let's take a look: Performance New Latest Intel hardware support - Harnessing the latest in chip-level support for virtualization, VirtualBox 3.2 supports new Intel Core i5 and i7 processor and Intel Xeon processor 5600 Series support for Unrestricted Guest Execution bringing faster boot times for everything from Windows to Solaris guests; New Large Page support - Reducing the size and overhead of key system resources, Large Page support delivers increased performance by enabling faster lookups and shorter table creation times. New In-hypervisor Networking - Significant optimization of the networking subsystem has reduced context switching between guests and host, increasing network throughput by up to 25%. New New Storage I/O subsystem - VirtualBox 3.2 offers a completely re-worked virtual disk subsystem which utilizes asynchronous I/O to achieve high-performance whilst maintaining high data integrity; New Remote Video Acceleration - The unique built-in VirtualBox Remote Display Protocol (VRDP), which is primarily used in virtual desktop infrastructure deployments, has been enhanced to deliver video acceleration. This delivers a rich user experience coupled with reduced computational expense, which is vital when servers are running hundreds of virtual machines; Power New Page Fusion - Traditional Page Sharing techniques have suffered from long and expensive cache construction as pages are scrutinized as candidates for de-duplication. Taking a smarter approach, VirtualBox Page Fusion uses intelligence in the guest virtual machine to determine much more rapidly and accurately those pages which can be eliminated thereby increasing the capacity or vm density of the system; New Memory Ballooning- Ballooning provides another method to increase vm density by allowing the memory of one guest to be recouped and made available to others; New Multiple Virtual Monitors - VirtualBox 3.2 now supports multi-headed virtual machines with up to 8 virtual monitors attached to a guest. Each virtual monitor can be a host window, or be mapped to the hosts physical monitors; New Hot-plug CPU's - Modern operating systems such Windows Server 2008 x64 Data Center Edition or the latest Linux server platforms allow CPUs to be dynamically inserted into a system to provide incremental computing power while the system is running. Version 3.2 introduces support for Hot-plug vCPUs, allowing VirtualBox virtual machines to be given more power, with zero-downtime of the guest; New Virtual SAS Controller - VirtualBox 3.2 now offers a virtual SAS controller, enabling it to run the most demanding of high-end guests; New Online Snapshot Merging - Snapshots are powerful but can eat up disk space and need to be pruned from time to time. Historically, machines have needed to be turned off to delete or merge snapshots but with VirtualBox 3.2 this operation can be done whilst the machines are running. This allows sophisticated system management with minimal interruption of operations; New OVF Enhancements - VirtualBox has supported the OVF standard for virtual machine portability for some time. Now with 3.2, VirtualBox specific configuration data is also stored in the standard allowing richer virtual machine definitions without compromising portability; New Guest Automation - The Guest Automation APIs allow host-based logic to drive operations in the guest; Platforms New USB Keyboard and Mouse - Support more guests that require USB input devices; New Oracle Enterprise Linux 5.5 - Support for the latest version of Oracle's flagship Linux platform; New Ubuntu 10.04 ("Lucid Lynx") - Support for both the desktop and server version of the popular Ubuntu Linux distribution; And as a man once said, "just one more thing" ... New Mac OS X (experimental) - On Apple hardware only, support for creating virtual machines run Mac OS X. All in all this is a pretty powerful release packed full of innovation and speedups. So what are you waiting for?  -FB 

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• BI&EPM in Focus Sep 2012

  - by Mike.Hallett(at)Oracle-BI&EPM

  Customers ·       Iluka Resources Improves Business Insight into Mining Operations Through Significantly Faster, Customized Analyses ·       Waikato Regional Council Consolidates Financial Reports up to 10 Times Faster  ·       Lojas Renner Shortens Budget Consolidation from Three Days to 15 Minutes; Improves Data Quality, and Supports Aggressive Expansion Plans  ·       Link to Complete Archive ·       Profit Magazine article featuring General Dynamics: RECONnomics: Integrate. Innovate. Grow (link) ·       Video: Goodhope Asia Unifies Financial Data with Oracle Hyperion (link)   Enterprise Performance Management ·       Oracle University Training on Demand: 1.     Oracle Hyperion Financial Reporting 11.1.2 for Financial Management (link) 2.     Oracle Essbase Bootcamp: On Demand (link) 3.     Oracle Hyperion Planning 11.1.2: Create & Manage Applications On Demand (link)   Business Intelligence ·       Oracle University Training on Demand: 1.     Learn How to Create Analyses, Dashboards with OBI 11g (link) 2.     Build Repositories with Oracle Business Intelligence 11g (link) 3.     Oracle BI Publisher 11g Fundamentals (link) 4.     Oracle BI Applications Courses now available for 7.9.6  (link) 5.     Oracle BI 11g: New Features and Exalytics ·       Oracle Business Intelligence Release 11.1.1.6.2BP, updated information: 1.     Oracle BI Mobile at the Speed of Thought 2.     What's New in Oracle Business Intelligence Mobile 3.     What's New in Oracle Business Intelligence Visualizations 4.     Oracle Business Intelligence on Oracle.com 5.     Download the New Release ·       Discover How to Turn Data into Insight: Big Data Guide : Whitepaper and set of short Videos. ·       New OPN Specialisation Exam for OBI 11g Certification . ·       Lastest BIC2g and Exalytics Demonstration VMs for Partners . ·       New Version 2.3 Oracle Endeca Information Discovery and Server now available . ·       New Oracle BI Publisher 11.1.1.6 Trial Edition Now Available .

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• Top Three Reasons to Move to the Cloud Before Your Next Upgrade

  - by yaldahhakim

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif";} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif";} 1) Reduced Cost - During major upgrades, most organizations typically need to replace or invest in extra hardware and other IT resources to support the upgrade. With the Cloud, this can become more of an Op-ex discussion. The flexibility and scalability of the cloud also allows for new business solution to be set up more quickly with the ability to scale IT resources to closely map to changing business requirements. . This enables more and faster innovation because you are spending money to focus on core business initiatives instead of setting up complex environments. 2) Reduced Risk- This is especially true when you are working with a cloud provider that possesses substantial in-house expertise. Oracle Managed Cloud Services has been hosting and managing customer’s business applications for over a decade and has help hundreds of customers upgrade and adopt new technologies faster and better. Customer have access to over 15,000 Oracle experts in operation centers around the world that can work around the clock and have direct access Oracle Development to optimize our customers’ upgrade experience. 3) Reduced Downtime - Whether a customer is looking to upgrade their E-Business Suite, PeopleSoft, JD-Edwards, or Fusion applications, we’ve developed standardized best practices and tools across the technology stack to accelerate the upgrade and migration with substantially reduced timelines and risk. And because the process is repeatable, customer stay more current on the latest releases, continuously taking advantage of the newest innovations – without the headache.. By leveraging the economies and expertise of scale that belong to Oracle, you can sleep better at night knowing that your next major application upgrade is taken care of. Check out the video of this Managed Cloud Services customer to learn more about their experience.

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• Creating a voxel world with 3D arrays using threads

  - by Sean M.

  I am making a voxel game (a bit like Minecraft) in C++(11), and I've come across an issue with creating a world efficiently. In my program, I have a World class, which holds a 3D array of Region class pointers. When I initialize the world, I give it a width, height, and depth so it knows how large of a world to create. Each Region is split up into a 32x32x32 area of blocks, so as you may guess, it takes a while to initialize the world once the world gets to be above 8x4x8 Regions. In order to alleviate this issue, I thought that using threads to generate different levels of the world concurrently would make it go faster. Having not used threads much before this, and being still relatively new to C++, I'm not entirely sure how to go about implementing one thread per level (level being a xz plane with a height of 1), when there is a variable number of levels. I tried this: for(int i = 0; i < height; i++) { std::thread th(std::bind(&World::load, this, width, height, depth)); th.join(); } Where load() just loads all Regions at height "height". But that executes the threads one at a time (which makes sense, looking back), and that of course takes as long as generating all Regions in one loop. I then tried: std::thread t1(std::bind(&World::load, this, w, h1, h2 - 1, d)); std::thread t2(std::bind(&World::load, this, w, h2, h3 - 1, d)); std::thread t3(std::bind(&World::load, this, w, h3, h4 - 1, d)); std::thread t4(std::bind(&World::load, this, w, h4, h - 1, d)); t1.join(); t2.join(); t3.join(); t4.join(); This works in that the world loads about 3-3.5 times faster, but this forces the height to be a multiple of 4, and it also gives the same exact VAO object to every single Region, which need individual VAOs in order to render properly. The VAO of each Region is set in the constructor, so I'm assuming that somehow the VAO number is not thread safe or something (again, unfamiliar with threads). So basically, my question is two one-part: How to I implement a variable number of threads that all execute at the same time, and force the main thread to wait for them using join() without stopping the other threads? How do I make the VAO objects thread safe, so when a bunch of Regions are being created at the same time across multiple threads, they don't all get the exact same VAO? Turns out it has to do with GL contexts not working across multiple threads. I moved the VAO/VBO creation back to the main thread. Fixed! Here is the code for block.h/.cpp, region.h/.cpp, and CVBObject.h/.cpp which controls VBOs and VAOs, in case you need it. If you need to see anything else just ask. EDIT: Also, I'd prefer not to have answers that are like "you should have used boost". I'm trying to do this without boost to get used to threads before moving onto other libraries.

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• Making user input/math on data fast, unlike excel type programs

  - by proGrammar

  I'm creating a research platform solely for myself to do some research on data. Programs like excel are terribly slow for me so I'm trying to come up with another solution. Originally I used excel. A1 was the cell that contained the data and all other cells in use calculated something on A1, or on other cells, that all could be in the end traced to A1. A1 was like an element of an array, I then I incremented it to go through all my data. This was way too slow. So the only other option I found originally was to hand code in c# the calculations inside a loop. Then I simply recompiled each time I changed my math. This was terribly slow to do and I had to order everything correctly so things would update correctly (dependencies). I could have also used events, but hand coding events for each cell like calculation would also be very slow. Next I created an application to read Excel and to perfectly imitate it. Which is what I now use. Basically I write formulas onto a fraction of my data to get live results inside excel. Then my program reads excel, writes another c# program, compiles it, and runs that program which runs my excel created formulas through a lot more data a whole lot faster. The advantage being my application dependency sorts everything (or I could use events) so I don't have to (like excel does) And of course the speed. But now its not a single application anymore. Instead its 2 applications, one which only reads my formulas and writes another program. The other one being the result which only lives for a short while before I do other runs through my data with different formulas / settings. So I can't see multiple results at one time without introducing even more programs like a database or at least having the 2 applications talking to each other. My idea was to have a dll that would be written, compiled, loaded, and unloaded again and again. So a self-updating program, sort of. But apparently that's not possible without another appdomain which means data has to be marshaled to be moved between the appdomains. Which would slow things down, not for summaries, but for other stuff I need to do with all my data. I'm also forgetting to mention a huge problem with restarting an application again and again which is having to reload ALL my data into memory again and again. But its still a whole lot faster than excel. I'm really super puzzled as to what people do when they want to research data fast. I'm completely unable to have a program accept user input and having it fast. My understanding is that it would have to do things like excel which is to evaluate strings again and again. So my only option is to repeatedly compile applications. Do I have a correct understanding on computer science? I've only just began programming, and didn't think I would have to learn much to do some simple math on data. My understanding is its either compiling my user defined stuff to a program or evaluating them from a string or something stupid again and again. And my only option is to probably switch operating systems or something to be able to have a program compile and run itself without stopping (writing/compiling dll, loading dll to program, unloading, and repeating). Can someone give me some idea on how computers work? Is anything better possible? Like a running program, that can accept user input and compile it and then unload it later? I mean heck operating systems dont need to be RESTARTED with every change to user input. What is this the cave man days? Sorry, it's just so super frustrating not knowing what one can do, and can't do. If only I could understand and learn this stuff fast enough.

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• Is make -j distcc possible to scale over 5 times?

  - by holmes

  Since distcc cannot keep states and just possible to send jobs and headers and let those servers to use only the data just sent and preprocess and compile, I think the lastest distcc has problem in scalability. In my local build environment which has appx. 10,000 c/c++ files to build, I could only make 2 times faster than not using distcc (but using make -j) when having 20 build servers. What do you think is the problem? If anyone has achieved scalability more than 10 - 20 times using make -j and distcc, please let me know. The following product claims that it is impossible to scale make -j and distcc faster than 5 times. http://www.electric-cloud.com/products/electricaccelerator.php I think this can be improved by: Letting the distccd server to maintain sessions Tied to those sessions, they will cache their own header directories Preprocess will be done demand base from the distccd server This will be done through a LD_PRELOADed library libdistcc.so which will replace stat/open syscalls and fetches the header files over network. ... Has anyone done this kind of thing?

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• jQuery AJAX slow in Firefox, fast in IE

  - by Brandon Montgomery

  I'm using jQuery to post to an ASP .NET Web Service to implement a custom auto-complete function. The code works great, except it's slow in FireFox (can't get it to go faster than 1 second). IE is blazing fast - works great. I watch the post in Firefox using Firebug. Here's the service code: <ScriptService(), _ WebService(Namespace:="http://tempuri.org/"), _ WebServiceBinding(ConformsTo:=WsiProfiles.BasicProfile1_1), _ ToolboxItem(False)> _ Public Class TestWebSvc Inherits System.Web.Services.WebService <WebMethod(), _ ScriptMethod(ResponseFormat:=Script.Services.ResponseFormat.Json, UseHttpGet:=True)> _ Public Function GetAccounts(ByVal q As String) As Object 'Code taken out for simplicity Return result End Function End Class And the jQuery ajax call: $.ajax({ beforeSend: function (req) { req.setRequestHeader("Content-Type", "application/json"); }, contentType: "application/json; charset=utf-8", type: "GET", url: "http://localhost/Suggest/TestWebSvc.asmx/GetAccounts", data: "q='" + element.val() + "'", dataType: "json", success: testWebSvcSuccess }); As you can see, I've tried to use the HTTP GET verb instead in hopes that that would make the call faster. As it does not, I'll probably switch it back to using POST if I can. Right now I'm just focused on why it's super fast in IE and super slow in Firefox. Versions: jQuery 1.3.2; Firefox 3.0.11; IE 8.0.6001.18783 (64-bit) Thank you for any insight you can provide.

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• Async.Parallel or Array.Parallel.Map ?

  - by gurteen2

  Hello- I'm trying to implement a pattern I read from Don Syme's blog (http://blogs.msdn.com/dsyme/archive/2010/01/09/async-and-parallel-design-patterns-in-f-parallelizing-cpu-and-i-o-computations.aspx) which suggests that there are opportunities for massive performance improvements from leveraging asynchronous I/O. I am currently trying to take a piece of code that "works" one way, using Array.Parallel.Map, and see if I can somehow achieve the same result using Async.Parallel, but I really don't understand Async.Parallel, and cannot get anything to work. I have a piece of code (simplified below to illustrate the point) that successfully retrieves an array of data for one cusip. (A price series, for example) let getStockData cusip = let D = DataProvider() let arr = D.GetPriceSeries(cusip) return arr let data = Array.Parallel.map (fun x -> getStockData x) stockCusips So this approach contructs an array of arrays, by making a connection over the internet to my data vendor for each stock (which could be as many as 3000) and returns me an array of arrays (1 per stock, with a price series for each one). I admittedly don't understand what goes on underneath Array.Parallel.map, but am wondering if this is a scenario where there are resources wasted under the hood, and it actually could be faster using asynchronous I/O? So to test this out, I have attempted to make this function using asyncs, and I think that the function below follows the pattern in Don Syme's article using the URLs, but it won't compile with "let!". let getStockDataAsync cusip = async { let D = DataProvider() let! arr = D.GetData(cusip) return arr } The error I get is: This expression was expected to have type Async<'a but here has type obj It compiles fine with "let" instead of "let!", but I had thought the whole point was that you need the exclamation point in order for the command to run without blocking a thread. So the first question really is, what's wrong with my syntax above, in getStockDataAsync, and then at a higher level, can anyone offer some additional insight about asychronous I/O and whether the scenario I have presented would benefit from it, making it potentially much, much faster than Array.Parallel.map? Thanks so much.

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• Encoding a email address that can be used as part of a URL in codeigniter

  - by freedayum

  Is there a way to encode a email address that can be used as a part of a url in codeigniter?. I need to decode back the email address from the url. What I am trying to do is just a -forgotten password recovery- thing. I send a confirmation link to the user's email address, the link needs to be like ../encodedEmail/forgottenPasswordCode (with the forgottenPasswordCode updated in the db for the user with the submitted email). When the user visits that link, I decode the email(if the email - forgottenPasswordCode pair is in the table), i allow them to reset their password (and i reset forgottenPasswordCode back to null). I could just do a loop -checking the table with a select query- (or) -set that forgottenPasswordCode column unique, so i keep generating on a insert failure(would that be a lot faster ?)- until I generate a forgottenPasswordCode that doesn't already exist in the table. But the guy I do this for would not accept it this way:). He wants the checking be done with the user's email, he thinks its much faster. I am working with codeigniter, I used its encode() function, it seems to produce characters like '-slashes-' at times that breaks the encoded-email-string. Any other ideas?

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• Opinions on Unladen Swallow?

  - by vartec

  What are your opinions and expectations on Google's Unladen Swallow? From their project plan: We want to make Python faster, but we also want to make it easy for large, well-established applications to switch to Unladen Swallow. Produce a version of Python at least 5x faster than CPython. Python application performance should be stable. Maintain source-level compatibility with CPython applications. Maintain source-level compatibility with CPython extension modules. We do not want to maintain a Python implementation forever; we view our work as a branch, not a fork. And even sweeter: In addition, we intend to remove the GIL and fix the state of multithreading in Python. We believe this is possible through the implementation of a more sophisticated GC It almost looks too good to be true, like the best of PyPy and Stackless combined. More info: Jesse Noller: "Pycon: Unladen-Swallow" ArsTechnica: "Google searches for holy grail of Python performance" Update: as DNS pointed out, there was related question: http://stackoverflow.com/questions/695370/what-is-llvm-and-how-is-replacing-python-vm-with-llvm-increasing-speeds-5x

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• Why are floating point values so prolific?

  - by Kibbee

  So, title says it all. Why are floating point values so prolific in computer programming. Due to problems like rounding errors, and not being able to even accurately represent numbers such as 0.1, I really can't see how they got as far as they did. I understand that the computation is faster with floating point numbers, however, I can think of only a few cases that they actually the right data type would be using. If you sat back and think about every time you used a floating point value, how many times did you say, well, some error would be ok, as long as the result was a few microseconds faster. It really makes me think because Jeff was talking about NP completeness, and how heuristics give an answer that is kind of right. And well, computers shouldn't do that. They should give you the answer that is correct. Yet we see floating point values used in many applications where they are completely not valid. What really bugs me, isn't that floating point exists, but that in many languages, there isn't even a viable alternative, non-floating point, decimal value. A lot of programmers when doing financial applications have to fall back to storing the number of cents in an integer field. Which brings with it all kinds of other problems. Why do floats continue to be so prolific, even though they can't represent the real answer, and we expect computers to be accurate? [EDIT] Just to clarify, I was talking about Base 2 floating points, and not base 10 floating points. .Net offers the Decimal data type, which is a base 10 floating point value which offers a much better representation of the numbers we deal with on a daily basis in most computer programs. I find it hard to believe that even modern languages like Java don't support base 10 floating point values, unless you want to move into the realm of things like BigDecimal, which isn't really the right answer either in a lot of situations.

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• Could CouchDB benefit significantly from the use of BERT instead of JSON?

  - by Victor Rodrigues

  I appreciate a lot CouchDB attempt to use universal web formats in everything it does: RESTFUL HTTP methods in every interaction, JSON objects, javascript code to customize database and documents. CouchDB seems to scale pretty well, but the individual cost to make a request usually makes 'relational' people afraid of. Many small business applications should deal with only one machine and that's all. In this case the scalability talk doesn't say too much, we need more performance per request, or people will not use it. BERT (Binary ERlang Term http://bert-rpc.org/ ) has proven to be a faster and lighter format than JSON and it is native for Erlang, the language in which CouchDB is written. Could we benefit from that, using BERT documents instead of JSON ones? I'm not saying just for retrieving in views, but for everything CouchDB does, including syncing. And, as a consequence of it, use Erlang functions instead of javascript ones. This would modify some original CouchDB principles, because today it is very web oriented. Considering I imagine few people would make their database API public and usually its data is accessed by the users through an application, it would be a good deal to have the ability to configure CouchDB for working faster. HTTP+JSON calls could still be handled by CouchDB, considering an extra cost in these cases because of parsing.

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• General question about DirectShow.NET, DirectShow and Windows Media Format

  - by Paul Andrews

  I searched and googled for an answer but couldn't find one. Basically I'm developing a webcam/audio streaming application which should capture audio and video from a pc (usb webcam/microphone) and send them to a receiving server. What the server will do with that it's another story and phase two (which I'm skipping for now) I wrote some code using DirectShow and Windows Media Format and it worked great for capture audio/video and sending them to another client, but there's a major problem: latency. Everywhere in the internet everyone gave me the same answer: "sorry dude but media format isn't for video conferencing, their codecs have too high latency". I thought I could skip the .wmv problems but seems like it's not possible to do... this road ends here then. So I saw a few examples with DirectShow.NET which were faster for both audio and video.. my question is: how come that DirectShow.NET is faster and better for video/audio conferencing? Shouldn't it be just a .NET porting of C++'s DirectShow? Am I missing something? I'm a bit confused at this point

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• Interface Casting vs. Class Casting

  - by Legatou

  I've been led to believe that casting can, in certain circumstances, become a measurable hindrance on performance. This may be moreso the case when we start dealing with incoherent webs of nasty exception throwing\catching. Given that I wish to create more correct heuristics when it comes to programming, I've been prompted to ask this question to the .NET gurus out there: Is interface casting faster than class casting? To give a code example, let's say this exists: public interface IEntity { IParent DaddyMommy { get; } } public interface IParent : IEntity { } public class Parent : Entity, IParent { } public class Entity : IEntity { public IParent DaddyMommy { get; protected set; } public IParent AdamEve_Interfaces { get { IEntity e = this; while (this.DaddyMommy != null) e = e.DaddyMommy as IEntity; return e as IParent; } } public Parent AdamEve_Classes { get { Entity e = this; while (this.DaddyMommy != null) e = e.DaddyMommy as Entity; return e as Parent; } } } So, is AdamEve_Interfaces faster than AdamEve_Classes? If so, by how much? And, if you know the answer, why?

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• Java repaint is slow under certain conditions.

  - by Gabriel A. Zorrilla

  I'm doing a simple grid which each square is highlighted by the cursor: They are a couple of JPanels, mapgrid and overlay inside a JLayeredPane, with mapgrid on the bottom. Mapgrid just draws on initialization the grid, its paint metodh is: public void paintComponent(Graphics g) { super.paintComponent(g); Graphics2D g2d = (Graphics2D) g; g2d.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON); for (int i = 0; i < h; i++) { for (int j = 0; j < w; j++) { g2d.setColor(new Color(128, 128, 128, 255)); g2d.drawRect(tileSize * j, i * tileSize, tileSize, tileSize); } } In the overlay JPanel is where the highlighting occurs, this is what is repainted when the mouse is moved: public void paintComponent(Graphics g) { super.paintComponent(g); Graphics2D g2d = (Graphics2D) g; g2d.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON); g2d.setColor(new Color(255, 255, 128, 255)); g2d.drawRect((pointerX/tileSize)*tileSize,(pointerY/ tileSize)*tileSize, tileSize, tileSize); } I noticed that even though the base layer (mapgrid) is NOT repainted when the mouse moves, just the transparent overlay layer, the performance is lacking. If i give the overlay JPanel a background, its way faster. If i remove the mapgrid Antialiasing, its a bit faster too. I don't know why giving a background to the overlay layer (and thus, hiding the mapgrid) or disabling antialiasing in the mapgrid leads to much better performance. Is there a better way to do this? Why does this happen?

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• haskell: a data structure for storing ascending integers with a very fast lookup

  - by valya

  Hello! (This question is related to my previous question, or rather to my answer to it.) I want to store all qubes of natural numbers in a structure and look up specific integers to see if they are perfect cubes. For example, cubes = map (\x -> x*x*x) [1..] is_cube n = n == (head $ dropWhile (<n) cubes) It is much faster than calculating the cube root, but It has complexity of O(n^(1/3)) (am I right?). I think, using a more complex data structure would be better. For example, in C I could store a length of an already generated array (not list - for faster indexing) and do a binary search. It would be O(log n) with lower ?oefficient than in another answer to that question. The problem is, I can't express it in Haskell (and I don't think I should). Or I can use a hash function (like mod). But I think it would be much more memory consuming to have several lists (or a list of lists), and it won't lower the complexity of lookup (still O(n^(1/3))), only a coefficient. I thought about a kind of a tree, but without any clever ideas (sadly I've never studied CS). I think, the fact that all integers are ascending will make my tree ill-balanced for lookups. And I'm pretty sure this fact about ascending integers can be a great advantage for lookups, but I don't know how to use it properly (see my first solution which I can't express in Haskell).

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• Bubble sort algorithm implementations (Haskell vs. C)

  - by kingping

  Hello. I have written 2 implementation of bubble sort algorithm in C and Haskell. Haskell implementation: module Main where main = do contents <- readFile "./data" print "Data loaded. Sorting.." let newcontents = bubblesort contents writeFile "./data_new_ghc" newcontents print "Sorting done" bubblesort list = sort list [] False rev = reverse -- separated. To see rev2 = reverse -- who calls the routine sort (x1:x2:xs) acc _ | x1 > x2 = sort (x1:xs) (x2:acc) True sort (x1:xs) acc flag = sort xs (x1:acc) flag sort [] acc True = sort (rev acc) [] False sort _ acc _ = rev2 acc I've compared these two implementations having run both on file with size of 20 KiB. C implementation took about a second, Haskell — about 1 min 10 sec. I have also profiled the Haskell application: Compile for profiling: C:\Temp ghc -prof -auto-all -O --make Main Profile: C:\Temp Main.exe +RTS -p and got these results. This is a pseudocode of the algorithm: procedure bubbleSort( A : list of sortable items ) defined as: do swapped := false for each i in 0 to length(A) - 2 inclusive do: if A[i] > A[i+1] then swap( A[i], A[i+1] ) swapped := true end if end for while swapped end procedure I wonder if it's possible to make Haskell implementation work faster without changing the algorithm (there's are actually a few tricks to make it work faster, but neither implementations have these optimizations)

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• High-concurrency counters without sharding

  - by dound

  This question concerns two implementations of counters which are intended to scale without sharding (with a tradeoff that they might under-count in some situations): http://appengine-cookbook.appspot.com/recipe/high-concurrency-counters-without-sharding/ (the code in the comments) http://blog.notdot.net/2010/04/High-concurrency-counters-without-sharding My questions: With respect to #1: Running memcache.decr() in a deferred, transactional task seems like overkill. If memcache.decr() is done outside the transaction, I think the worst-case is the transaction fails and we miss counting whatever we decremented. Am I overlooking some other problem that could occur by doing this? What are the significiant tradeoffs between the two implementations? Here are the tradeoffs I see: #2 does not require datastore transactions. To get the counter's value, #2 requires a datastore fetch while with #1 typically only needs to do a memcache.get() and memcache.add(). When incrementing a counter, both call memcache.incr(). Periodically, #2 adds a task to the task queue while #1 transactionally performs a datastore get and put. #1 also always performs memcache.add() (to test whether it is time to persist the counter to the datastore). Conclusions (without actually running any performance tests): #1 should typically be faster at retrieving a counter (#1 memcache vs #2 datastore). Though #1 has to perform an extra memcache.add() too. However, #2 should be faster when updating counters (#1 datastore get+put vs #2 enqueue a task). On the other hand, with #1 you have to be a bit more careful with the update interval since the task queue quota is almost 100x smaller than either the datastore or memcahce APIs.

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• Python pixel manipulation library

  - by silinter

  So I'm going through the beginning stages of producing a game in Python, and I'm looking for a library that is able to manipulate pixels and blit them relatively fast. My first thought was pygame, as it deals in pure 2D surfaces, but it only allows pixel access through pygame.get_at(), pygame.set_at() and pygame.get_buffer(), all of which lock the surface each time they're called, making them slow to use. I can also use the PixelArray and surfarray classes, but they are locked for the duration of their lifetimes, and the only way to blit them to a surface is to either copy the pixels to a new surface, or use surfarray.blit_array, which requires creating a subsurface of the screen and blitting it to that, if the array is smaller than the screen (if it's bigger I can just use a slice of the array, which is no problem). I don't have much experience with PyOpenGL or Pyglet, but I'm wondering if there is a faster library for doing pixel manipulation in, or if there is a faster method, in Pygame, for doing pixel manupilation. I did some work with SDL and OpenGL in C, and I do like the idea of adding vertex/fragment shaders to my program. My program will chiefly be dealing in loading images and writing/reading to/from surfaces.

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• SQL Server Multi-statement UDF - way to store data temporarily required

  - by Kharlos Dominguez

  Hello, I have a relatively complex query, with several self joins, which works on a rather large table. For that query to perform faster, I thus need to only work with a subset of the data. Said subset of data can range between 12 000 and 120 000 rows depending on the parameters passed. More details can be found here: http://stackoverflow.com/questions/3054843/sql-server-cte-referred-in-self-joins-slow As you can see, I was using a CTE to return the data subset before, which caused some performance problems as SQL Server was re-running the Select statement in the CTE for every join instead of simply being run once and reusing its data set. The alternative, using temporary tables worked much faster (while testing the query in a separate window outside the UDF body). However, when I tried to implement this in a multi-statement UDF, I was harshly reminded by SQL Server that multi-statement UDFs do not support temporary tables for some reason... UDFs do allow table variables however, so I tried that, but the performance is absolutely horrible as it takes 1m40 for my query to complete whereas the the CTE version only took 40minutes. I believe the table variables is slow for reasons listed in this thread: http://stackoverflow.com/questions/1643687/table-variable-poor-performance-on-insert-in-sql-server-stored-procedure Temporary table version takes around 1 seconds, but I can't make it into a function due to the SQL Server restrictions, and I have to return a table back to the caller. Considering that CTE and table variables are both too slow, and that temporary tables are rejected in UDFs, What are my options in order for my UDF to perform quickly? Thanks a lot in advance.

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• Fastest way to generate delimited string from 1d numpy array

  - by Abiel

  I have a program which needs to turn many large one-dimensional numpy arrays of floats into delimited strings. I am finding this operation quite slow relative to the mathematical operations in my program and am wondering if there is a way to speed it up. For example, consider the following loop, which takes 100,000 random numbers in a numpy array and joins each array into a comma-delimited string. import numpy as np x = np.random.randn(100000) for i in range(100): ",".join(map(str, x)) This loop takes about 20 seconds to complete (total, not each cycle). In contrast, consider that 100 cycles of something like elementwise multiplication (x*x) would take than one 1/10 of a second to complete. Clearly the string join operation creates a large performance bottleneck; in my actual application it will dominate total runtime. This makes me wonder, is there a faster way than ",".join(map(str, x))? Since map() is where almost all the processing time occurs, this comes down to the question of whether there a faster to way convert a very large number of numbers to strings.

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• Flash CS4 compiler Error 1120 when embedding pngs into class instance variables.

  - by theolagendijk

  I have a Flash CS4 (Flash 9 ActionScript 3.0) project that compiles and runs perfectly on my machine. However it is part of a big batch of fla's that I want to compile on another (faster) machine. When I copy the project (the fla and all actionscripts and assets files) to the faster machine, it's Flash CS4 compiler gives me compiler error 1120 "Access of undefined property ButtonPause_PauseNormal". The property "PauseNormal" is an embedded png. The PNG is available. No transcoder errors. Here's the ActionScript for class "ButtonPause"; package nl.platipus.NissanESM.buttons { import flash.display.*; import flash.events.*; public class ButtonPause extends Sprite { [Embed(source="../../../../player/pause.png")] private var PauseNormal:Class; [Embed(source="../../../../player/pause_mo.png")] private var PauseMouseOver:Class; private var stateNormal:Bitmap; private var stateMouseOver:Bitmap; public function ButtonPause() { stateNormal = new PauseNormal(); stateNormal.width = 29; stateNormal.height = 14; stateNormal.alpha = 1; addChild(stateNormal); stateMouseOver = new PauseMouseOver(); stateMouseOver.width = 29; stateMouseOver.height = 14; stateMouseOver.alpha = 0; addChild(stateMouseOver); width = 29; height = 14; addEventListener(MouseEvent.MOUSE_OVER, handleMouseOver); addEventListener(MouseEvent.MOUSE_OUT, handleMouseOut ); } private function handleMouseOver(evt:MouseEvent):void { stateNormal.alpha = 0; stateMouseOver.alpha = 1; } private function handleMouseOut(evt:MouseEvent):void { stateNormal.alpha = 1; stateMouseOver.alpha = 0; } } } (Both machines run the exact same Flash CS4 Profesional Version 10.0.2 installation and both have the exact same publish settings and ActionScript 3.0 settings.) What's going on?

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• SQL with Regular Expressions vs Indexes with Logical Merging Functions

  - by geeko

  Hello Lads, I am trying to develop a complex textual search engine. I have thousands of textual pages from many books. I need to search pages that contain specified complex logical criterias. These criterias can contain virtually any compination of the following: A: Full words. B: Word roots (semilar to stems; i.e. all words with certain key letters). C: Word templates (in some languages are filled in certain templates to form various part of speech such as adjactives, past/present verbs...). D: Logical connectives: AND/OR/XOR/NOT/IF/IFF and parentheses to state priorities. Now, would it be faster to have the pages' full text in database (not indexed) and search though them all using SQL and Regular Expressions ? Or would it be better to construct indexes of word/root/template-page-location tuples. Hence, we can boost searching for individual words/roots/templates. However, it gets tricky as we interdouce logical connectives into our query. I thought of doing the following steps in such cases: 1: Seperately search for each individual words/roots/templates in the specified query. 2: On priority bases, we merge two result lists (from step 1) at a time depedning on the logical connective For example, if we are searching for "he AND (is OR was)": 1: We shall search for "he", "is" and "was" seperately and get result lists for each word. 2: Merge the result lists of "is" and "was" using the merging function OR-MERGE 3: Merge the merged result list from the OR-MERGE function with the one of "he" using the merging function AND-MERGE The result of step 3 is then returned as the result of the specified query. What do you think gurues ? Which is faster ? Any better ideas ? Thank you all in advance.

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• Why is curl in Ruby slower than command-line curl?

  - by Stiivi

  I am trying to download more than 1m pages (URLs ending by a sequence ID). I have implemented kind of multi-purpose download manager with configurable number of download threads and one processing thread. The downloader downloads files in batches: curl = Curl::Easy.new batch_urls.each { |url_info| curl.url = url_info[:url] curl.perform file = File.new(url_info[:file], "wb") file << curl.body_str file.close # ... some other stuff } I have tried to download 8000 pages sample. When using the code above, I get 1000 in 2 minutes. When I write all URLs into a file and do in shell: cat list | xargs curl I gen all 8000 pages in two minutes. Thing is, I need it to have it in ruby code, because there is other monitoring and processing code. I have tried: Curl::Multi - it is somehow faster, but misses 50-90% of files (does not download them and gives no reason/code) multiple threads with Curl::Easy - around the same speed as single threaded Why is reused Curl::Easy slower than subsequent command line curl calls and how can I make it faster? Or what I am doing wrong? I would prefer to fix my download manager code than to make downloading for this case in a different way. Before this, I was calling command-line wget which I provided with a file with list of URLs. Howerver, not all errors were handled, also it was not possible to specify output file for each URL separately when using URL list. Now it seems to me that the best way would be to use multiple threads with system call to 'curl' command. But why when I can use directly Curl in Ruby? Code for the download manager is here, if it might help: Download Manager (I have played with timeouts, from not-setting it to various values, it did not seem help) Any hints appreciated.

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• How close can I get C# to the performance of C++ for small intensive tasks?

  - by SLC

  I was thinking about the speed difference of C++ to C# being mostly about C# compiling to byte-code that is taken in by the JIT compiler (is that correct?) and all the checks C# does. I notice that it is possible to turn a lot of these functions off, both in the compile options, and possibly through using the unsafe keyword as unsafe code is not verifiable by the common language runtime. Therefore if you were to write a simple console application in both languages, that flipped an imaginary coin an infinite number of times and displayed the results to the screen every 10,000 or so iterations, how much speed difference would there be? I chose this because it's a very simple program. I'd like to test this but I don't know C++ or have the tools to compile it. This is my C# version though: static void Main(string[] args) { unsafe { Random rnd = new Random(); int heads = 0, tails = 0; while (true) { if (rnd.NextDouble() > 0.5) heads++; else tails++; if ((heads + tails) % 1000000 == 0) Console.WriteLine("Heads: {0} Tails: {1}", heads, tails); } } } Is the difference enough to warrant deliberately compiling sections of code "unsafe" or into DLLs that do not have some of the compile options like overflow checking enabled? Or does it go the other way, where it would be beneficial to compile sections in C++? I'm sure interop speed comes into play too then. To avoid subjectivity, I reiterate the specific parts of this question as: Does C# have a performance boost from using unsafe code? Do the compile options such as disabling overflow checking boost performance, and do they affect unsafe code? Would the program above be faster in C++ or negligably different? Is it worth compiling long intensive number-crunching tasks in a language such as C++ or using /unsafe for a bonus? Less subjectively, could I complete an intensive operation faster by doing this?

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