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  • Who could ask for more with LESS CSS? (Part 3 of 3&ndash;Clrizr)

    - by ToString(theory);
    Welcome back!  In the first two posts in this series, I covered some of the awesome features in CSS precompilers such as SASS and LESS, as well as how to get an initial project setup up and running in ASP.Net MVC 4. In this post, I will cover an actual advanced example of using LESS in a project, and show some of the great productivity features we gain from its usage. Introduction In the first post, I mentioned two subjects that I will be using in this example – constants, and color functions.  I’ve always enjoyed using online color scheme utilities such as Adobe Kuler or Color Scheme Designer to come up with a scheme based off of one primary color.  Using these tools, and requesting a complementary scheme you can get a couple of shades of your primary color, and a couple of shades of a complementary/accent color to display. Because there is no way in regular css to do color operations or store variables, there was no way to accomplish something like defining a primary color, and have a site theme cascade off of that.  However with tools such as LESS, that impossibility becomes a reality!  So, if you haven’t guessed it by now, this post is on the creation of a plugin/module/less file to drop into your project, plugin one color, and have your primary theme cascade from it.  I only went through the trouble of creating a module for getting Complementary colors.  However, it wouldn’t be too much trouble to go through other options such as Triad or Monochromatic to get a module that you could use off of that. Step 1 – Analysis I decided to mimic Adobe Kuler’s Complementary theme algorithm as I liked its simplicity and aesthetics.  Color Scheme Designer is great, but I do believe it can give you too many color options, which can lead to chaos and overload.  The first thing I had to check was if the complementary values for the color schemes were actually hues rotated by 180 degrees at all times – they aren’t.  Apparently Adobe applies some variance to the complementary colors to get colors that are actually more aesthetically appealing to users.  So, I opened up Excel and began to plot complementary hues based on rotation in increments of 10: Long story short, I completed the same calculations for Hue, Saturation, and Lightness.  For Hue, I only had to record the Complementary hue values, however for saturation and lightness, I had to record the values for ALL of the shades.  Since the functions were too complicated to put into LESS since they aren’t constant/linear, but rather interval functions, I instead opted to extrapolate the HSL values using the trendline function for each major interval, onto intervals of spacing 1. For example, using the hue extraction, I got the following values: Interval Function 0-60 60-140 140-270 270-360 Saturation and Lightness were much worse, but in the end, I finally had functions for all of the intervals, and then went the route of just grabbing each shades value in intervals of 1.  Step 2 – Mapping I declared variable names for each of these sections as something that shouldn’t ever conflict with a variable someone would define in their own file.  After I had each of the values, I extracted the values and put them into files of their own for hue variables, saturation variables, and lightness variables…  Example: /*HUE CONVERSIONS*/@clrizr-hue-source-0deg: 133.43;@clrizr-hue-source-1deg: 135.601;@clrizr-hue-source-2deg: 137.772;@clrizr-hue-source-3deg: 139.943;@clrizr-hue-source-4deg: 142.114;.../*SATURATION CONVERSIONS*/@clrizr-saturation-s2SV0px: 0;@clrizr-saturation-s2SV1px: 0;@clrizr-saturation-s2SV2px: 0;@clrizr-saturation-s2SV3px: 0;@clrizr-saturation-s2SV4px: 0;.../*LIGHTNESS CONVERSIONS*/@clrizr-lightness-s2LV0px: 30;@clrizr-lightness-s2LV1px: 31;@clrizr-lightness-s2LV2px: 32;@clrizr-lightness-s2LV3px: 33;@clrizr-lightness-s2LV4px: 34;...   In the end, I have 973 lines of mapping/conversion from source HSL to shade HSL for two extra primary shades, and two complementary shades. The last bit of the work was the file to compose each of the shades from these mappings. Step 3 – Clrizr Mapper The final step was the hardest to overcome as I was still trying to understand LESS to its fullest extent.  Imports As mentioned previously, I had separated the HSL mappings into different files, so the first necessary step is to import those for use into the Clrizr plugin: @import url("hue.less");@import url("saturation.less");@import url("lightness.less"); Extract Component Values For Each Shade Next, I extracted the necessary information for each shade HSL before shade composition: @clrizr-input-saturation: 1px+floor(saturation(@clrizr-input))-1;@clrizr-input-lightness: 1px+floor(lightness(@clrizr-input))-1; @clrizr-complementary-hue: formatstring("clrizr-hue-source-{0}", ceil(hue(@clrizr-input))); @clrizr-primary-2-saturation: formatstring("clrizr-saturation-s2SV{0}",@clrizr-input-saturation);@clrizr-primary-1-saturation: formatstring("clrizr-saturation-s1SV{0}",@clrizr-input-saturation);@clrizr-complementary-1-saturation: formatstring("clrizr-saturation-c1SV{0}",@clrizr-input-saturation); @clrizr-primary-2-lightness: formatstring("clrizr-lightness-s2LV{0}",@clrizr-input-lightness);@clrizr-primary-1-lightness: formatstring("clrizr-lightness-s1LV{0}",@clrizr-input-lightness);@clrizr-complementary-1-lightness: formatstring("clrizr-lightness-c1LV{0}",@clrizr-input-lightness); Here, you can see a couple of odd things…  On the first line, I am using operations to add units to the saturation and lightness.  This is due to some limitations in the operations that would give me saturation or lightness in %, which can’t be in a variable name.  So, I use first add 1px to it, which casts the result of the following functions as px instead of %, and then at the end, I remove that pixel.  You can also see here the formatstring method which is exactly what it sounds like – something like String.Format(string str, params object[] obj). Get Primary & Complementary Shades Now that I have components for each of the different shades, I can now compose them into each of their pieces.  For this, I use the @@ operator which will look for a variable with the name specified in a string, and then call that variable: @clrizr-primary-2: hsl(hue(@clrizr-input), @@clrizr-primary-2-saturation, @@clrizr-primary-2-lightness);@clrizr-primary-1: hsl(hue(@clrizr-input), @@clrizr-primary-1-saturation, @@clrizr-primary-1-lightness);@clrizr-primary: @clrizr-input;@clrizr-complementary-1: hsl(@@clrizr-complementary-hue, @@clrizr-complementary-1-saturation, @@clrizr-complementary-1-lightness);@clrizr-complementary-2: hsl(@@clrizr-complementary-hue, saturation(@clrizr-input), lightness(@clrizr-input)); That’s is it, for the most part.  These variables now hold the theme for the one input color – @clrizr-input.  However, I have one last addition… Perceptive Luminance Well, after I got the colors, I decided I wanted to also get the best font color that would go on top of it.  Black or white depending on light or dark color.  Now I couldn’t just go with checking the lightness, as that is half the story.  You see, the human eye doesn’t see ALL colors equally well but rather has more cells for interpreting green light compared to blue or red.  So, using the ratio, we can calculate the perceptive luminance of each of the shades, and get the font color that best matches it! @clrizr-perceptive-luminance-ps2: round(1 - ( (0.299 * red(@clrizr-primary-2) ) + ( 0.587 * green(@clrizr-primary-2) ) + (0.114 * blue(@clrizr-primary-2)))/255)*255;@clrizr-perceptive-luminance-ps1: round(1 - ( (0.299 * red(@clrizr-primary-1) ) + ( 0.587 * green(@clrizr-primary-1) ) + (0.114 * blue(@clrizr-primary-1)))/255)*255;@clrizr-perceptive-luminance-ps: round(1 - ( (0.299 * red(@clrizr-primary) ) + ( 0.587 * green(@clrizr-primary) ) + (0.114 * blue(@clrizr-primary)))/255)*255;@clrizr-perceptive-luminance-pc1: round(1 - ( (0.299 * red(@clrizr-complementary-1)) + ( 0.587 * green(@clrizr-complementary-1)) + (0.114 * blue(@clrizr-complementary-1)))/255)*255;@clrizr-perceptive-luminance-pc2: round(1 - ( (0.299 * red(@clrizr-complementary-2)) + ( 0.587 * green(@clrizr-complementary-2)) + (0.114 * blue(@clrizr-complementary-2)))/255)*255; @clrizr-col-font-on-primary-2: rgb(@clrizr-perceptive-luminance-ps2, @clrizr-perceptive-luminance-ps2, @clrizr-perceptive-luminance-ps2);@clrizr-col-font-on-primary-1: rgb(@clrizr-perceptive-luminance-ps1, @clrizr-perceptive-luminance-ps1, @clrizr-perceptive-luminance-ps1);@clrizr-col-font-on-primary: rgb(@clrizr-perceptive-luminance-ps, @clrizr-perceptive-luminance-ps, @clrizr-perceptive-luminance-ps);@clrizr-col-font-on-complementary-1: rgb(@clrizr-perceptive-luminance-pc1, @clrizr-perceptive-luminance-pc1, @clrizr-perceptive-luminance-pc1);@clrizr-col-font-on-complementary-2: rgb(@clrizr-perceptive-luminance-pc2, @clrizr-perceptive-luminance-pc2, @clrizr-perceptive-luminance-pc2); Conclusion That’s it!  I have posted a project on clrizr.codePlex.com for this, and included a testing page for you to test out how it works.  Feel free to use it in your own project, and if you have any questions, comments or suggestions, please feel free to leave them here as a comment, or on the contact page!

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  • CSS alignment differs per page, cant find reason [migrated]

    - by Floran
    I list products on my homepage and on a company details page. I use the exact same HTML, but for some reason the product appears different: The productname is "Artikel 1". Here the product is displayed correctly: http://www.zorgbeurs.nl/ Notice how the green price area is right below the product. But here: http://www.zorgbeurs.nl/bedrijven/76/mymedical the green price area is all the way at the bottom of the page. Why?

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  • Registration Open for 2015 Oracle Value Chain Summit

    - by Terri Hiskey
    Registration has opened for the Oracle Value Chain Summit, taking place January 26-28 in San Jose, California. Register now and take advantage of the Super Saver rate of only $495 (a $400 savings from the regular registration rate), good through September 26. Click here to register today, or to check out further information about the Summit. Keynote speakers to the 2015 event include former 49ers quarterback Steve Young and leading green business expert and author of the best-selling Green to Gold, Andrew Winston.

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  • argv Memory Allocation

    - by Joshua Green
    I was wondering if someone could tell me what I am doing wrong that I get this Unhandled Exception error message: 0xC0000005: Access violation reading location 0x0000000c. with a green pointer pointing at my first Prolog code (fid_t): Here is my header file: class UserTaskProlog { public: UserTaskProlog( ArRobot* r ); ~UserTaskProlog( ); protected: int cycles; char* argv[ 1 ]; term_t tf; term_t tx; term_t goal_term; functor_t goal_functor; ArRobot* robot; void logTask( ); }; And here is my main code: UserTaskProlog::UserTaskProlog( ArRobot* r ) : robot( r ), robotTaskFunc( this, &UserTaskProlog::logTask ) { cycles = 0; argv[ 0 ] = "libpl.dll"; argv[ 1 ] = NULL; PL_initialise( 1, argv ); PlCall( "consult( 'myPrologFile.pl' )" ); robot->addSensorInterpTask( "UserTaskProlog", 50, &robotTaskFunc ); } UserTaskProlog::~UserTaskProlog( ) { robot->remSensorInterpTask( &robotTaskFunc ); } void UserTaskProlog::logTask( ) { cycles++; fid_t fid = PL_open_foreign_frame( ); tf = PL_new_term_ref( ); PL_put_integer( tf, 5 ); tx = PL_new_term_ref( ); goal_term = PL_new_term_ref( ); goal_functor = PL_new_functor( PL_new_atom( "factorial" ), 2 ); PL_cons_functor( goal_term, goal_functor, tf, tx ); int fact; if ( PL_call( goal_term, NULL ) ) { PL_get_integer( tx, &fact ); cout << fact << endl; } PL_discard_foreign_frame( fid ); } int main( int argc, char** argv ) { ArRobot robot; ArArgumentParser argParser( &argc, argv ); UserTaskProlog talk( &robot ); } Thank you,

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  • Cutting objects and applying texture to cut. Unity3d/C#

    - by Timothy Williams
    Basically what I'm trying to do is figure out how to calculate realtime cutting of objects, and apply a texture to the cut. I found some good scripts, but most of them have been abandoned and aren't really fully working yet. Applying textures: http://forum.unity3d.com/threads/75949-Mesh-Real-Cutting?highlight=mesh+real+cutting Cutting: http://forum.unity3d.com/threads/78594-Object-Cutter Another (Free) Cutter (Also, I'm not entirely sure how this one will handle cutting complex meshes): http://forum.unity3d.com/threads/69992-fake-slicer?p=449114&viewfull=1#post449114 My plan as of right now is to combine links 1 & 2 or 1 & 3 programming wise. What I'm asking here for is any advice on how to advance (links to asset store packages, or other codes to show how to accomplish something complex like this.)

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  • CLR via C# 3rd Edition is out

    - by Abhijeet Patel
    Time for some book news update. CLR via C#, 3rd Edition seems to have been out for a little while now. The book was released in early Feb this year, and needless to say my copy is on it’s way. I can barely wait to dig in and chew on the goodies that one of the best technical authors and software professionals I respect has in store. The 2nd edition of the book was an absolute treat and this edition promises to be no less. Here is a brief description of what’s new and updated from the 2nd edition. Part I – CLR Basics Chapter 1-The CLR’s Execution Model Added about discussion about C#’s /optimize and /debug switches and how they relate to each other. Chapter 2-Building, Packaging, Deploying, and Administering Applications and Types Improved discussion about Win32 manifest information and version resource information. Chapter 3-Shared Assemblies and Strongly Named Assemblies Added discussion of TypeForwardedToAttribute and TypeForwardedFromAttribute. Part II – Designing Types Chapter 4-Type Fundamentals No new topics. Chapter 5-Primitive, Reference, and Value Types Enhanced discussion of checked and unchecked code and added discussion of new BigInteger type. Also added discussion of C# 4.0’s dynamic primitive type. Chapter 6-Type and Member Basics No new topics. Chapter 7-Constants and Fields No new topics. Chapter 8-Methods Added discussion of extension methods and partial methods. Chapter 9-Parameters Added discussion of optional/named parameters and implicitly-typed local variables. Chapter 10-Properties Added discussion of automatically-implemented properties, properties and the Visual Studio debugger, object and collection initializers, anonymous types, the System.Tuple type and the ExpandoObject type. Chapter 11-Events Added discussion of events and thread-safety as well as showing a cool extension method to simplify the raising of an event. Chapter 12-Generics Added discussion of delegate and interface generic type argument variance. Chapter 13-Interfaces No new topics. Part III – Essential Types Chapter 14-Chars, Strings, and Working with Text No new topics. Chapter 15-Enums Added coverage of new Enum and Type methods to access enumerated type instances. Chapter 16-Arrays Added new section on initializing array elements. Chapter 17-Delegates Added discussion of using generic delegates to avoid defining new delegate types. Also added discussion of lambda expressions. Chapter 18-Attributes No new topics. Chapter 19-Nullable Value Types Added discussion on performance. Part IV – CLR Facilities Chapter 20-Exception Handling and State Management This chapter has been completely rewritten. It is now about exception handling and state management. It includes discussions of code contracts and constrained execution regions (CERs). It also includes a new section on trade-offs between writing productive code and reliable code. Chapter 21-Automatic Memory Management Added discussion of C#’s fixed state and how it works to pin objects in the heap. Rewrote the code for weak delegates so you can use them with any class that exposes an event (the class doesn’t have to support weak delegates itself). Added discussion on the new ConditionalWeakTable class, GC Collection modes, Full GC notifications, garbage collection modes and latency modes. I also include a new sample showing how your application can receive notifications whenever Generation 0 or 2 collections occur. Chapter 22-CLR Hosting and AppDomains Added discussion of side-by-side support allowing multiple CLRs to be loaded in a single process. Added section on the performance of using MarshalByRefObject-derived types. Substantially rewrote the section on cross-AppDomain communication. Added section on AppDomain Monitoring and first chance exception notifications. Updated the section on the AppDomainManager class. Chapter 23-Assembly Loading and Reflection Added section on how to deploy a single file with dependent assemblies embedded inside it. Added section comparing reflection invoke vs bind/invoke vs bind/create delegate/invoke vs C#’s dynamic type. Chapter 24-Runtime Serialization This is a whole new chapter that was not in the 2nd Edition. Part V – Threading Chapter 25-Threading Basics Whole new chapter motivating why Windows supports threads, thread overhead, CPU trends, NUMA Architectures, the relationship between CLR threads and Windows threads, the Thread class, reasons to use threads, thread scheduling and priorities, foreground thread vs background threads. Chapter 26-Performing Compute-Bound Asynchronous Operations Whole new chapter explaining the CLR’s thread pool. This chapter covers all the new .NET 4.0 constructs including cooperative cancelation, Tasks, the aralle class, parallel language integrated query, timers, how the thread pool manages its threads, cache lines and false sharing. Chapter 27-Performing I/O-Bound Asynchronous Operations Whole new chapter explaining how Windows performs synchronous and asynchronous I/O operations. Then, I go into the CLR’s Asynchronous Programming Model, my AsyncEnumerator class, the APM and exceptions, Applications and their threading models, implementing a service asynchronously, the APM and Compute-bound operations, APM considerations, I/O request priorities, converting the APM to a Task, the event-based Asynchronous Pattern, programming model soup. Chapter 28-Primitive Thread Synchronization Constructs Whole new chapter discusses class libraries and thread safety, primitive user-mode, kernel-mode constructs, and data alignment. Chapter 29-Hybrid Thread Synchronization Constructs Whole new chapter discussion various hybrid constructs such as ManualResetEventSlim, SemaphoreSlim, CountdownEvent, Barrier, ReaderWriterLock(Slim), OneManyResourceLock, Monitor, 3 ways to solve the double-check locking technique, .NET 4.0’s Lazy and LazyInitializer classes, the condition variable pattern, .NET 4.0’s concurrent collection classes, the ReaderWriterGate and SyncGate classes.

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  • Talend Enterprise Data Integration overperforms on Oracle SPARC T4

    - by Amir Javanshir
    The SPARC T microprocessor, released in 2005 by Sun Microsystems, and now continued at Oracle, has a good track record in parallel execution and multi-threaded performance. However it was less suited for pure single-threaded workloads. The new SPARC T4 processor is now filling that gap by offering a 5x better single-thread performance over previous generations. Following our long-term relationship with Talend, a fast growing ISV positioned by Gartner in the “Visionaries” quadrant of the “Magic Quadrant for Data Integration Tools”, we decided to test some of their integration components with the T4 chip, more precisely on a T4-1 system, in order to verify first hand if this new processor stands up to its promises. Several tests were performed, mainly focused on: Single-thread performance of the new SPARC T4 processor compared to an older SPARC T2+ processor Overall throughput of the SPARC T4-1 server using multiple threads The tests consisted in reading large amounts of data --ten's of gigabytes--, processing and writing them back to a file or an Oracle 11gR2 database table. They are CPU, memory and IO bound tests. Given the main focus of this project --CPU performance--, bottlenecks were removed as much as possible on the memory and IO sub-systems. When possible, the data to process was put into the ZFS filesystem cache, for instance. Also, two external storage devices were directly attached to the servers under test, each one divided in two ZFS pools for read and write operations. Multi-thread: Testing throughput on the Oracle T4-1 The tests were performed with different number of simultaneous threads (1, 2, 4, 8, 12, 16, 32, 48 and 64) and using different storage devices: Flash, Fibre Channel storage, two stripped internal disks and one single internal disk. All storage devices used ZFS as filesystem and volume management. Each thread read a dedicated 1GB-large file containing 12.5M lines with the following structure: customerID;FirstName;LastName;StreetAddress;City;State;Zip;Cust_Status;Since_DT;Status_DT 1;Ronald;Reagan;South Highway;Santa Fe;Montana;98756;A;04-06-2006;09-08-2008 2;Theodore;Roosevelt;Timberlane Drive;Columbus;Louisiana;75677;A;10-05-2009;27-05-2008 3;Andrew;Madison;S Rustle St;Santa Fe;Arkansas;75677;A;29-04-2005;09-02-2008 4;Dwight;Adams;South Roosevelt Drive;Baton Rouge;Vermont;75677;A;15-02-2004;26-01-2007 […] The following graphs present the results of our tests: Unsurprisingly up to 16 threads, all files fit in the ZFS cache a.k.a L2ARC : once the cache is hot there is no performance difference depending on the underlying storage. From 16 threads upwards however, it is clear that IO becomes a bottleneck, having a good IO subsystem is thus key. Single-disk performance collapses whereas the Sun F5100 and ST6180 arrays allow the T4-1 to scale quite seamlessly. From 32 to 64 threads, the performance is almost constant with just a slow decline. For the database load tests, only the best IO configuration --using external storage devices-- were used, hosting the Oracle table spaces and redo log files. Using the Sun Storage F5100 array allows the T4-1 server to scale up to 48 parallel JVM processes before saturating the CPU. The final result is a staggering 646K lines per second insertion in an Oracle table using 48 parallel threads. Single-thread: Testing the single thread performance Seven different tests were performed on both servers. Given the fact that only one thread, thus one file was read, no IO bottleneck was involved, all data being served from the ZFS cache. Read File ? Filter ? Write File: Read file, filter data, write the filtered data in a new file. The filter is set on the “Status” column: only lines with status set to “A” are selected. This limits each output file to about 500 MB. Read File ? Load Database Table: Read file, insert into a single Oracle table. Average: Read file, compute the average of a numeric column, write the result in a new file. Division & Square Root: Read file, perform a division and square root on a numeric column, write the result data in a new file. Oracle DB Dump: Dump the content of an Oracle table (12.5M rows) into a CSV file. Transform: Read file, transform, write the result data in a new file. The transformations applied are: set the address column to upper case and add an extra column at the end, which is the concatenation of two columns. Sort: Read file, sort a numeric and alpha numeric column, write the result data in a new file. The following table and graph present the final results of the tests: Throughput unit is thousand lines per second processed (K lines/second). Improvement is the % of improvement between the T5140 and T4-1. Test T4-1 (Time s.) T5140 (Time s.) Improvement T4-1 (Throughput) T5140 (Throughput) Read/Filter/Write 125 806 645% 100 16 Read/Load Database 195 1111 570% 64 11 Average 96 557 580% 130 22 Division & Square Root 161 1054 655% 78 12 Oracle DB Dump 164 945 576% 76 13 Transform 159 1124 707% 79 11 Sort 251 1336 532% 50 9 The improvement of single-thread performance is quite dramatic: depending on the tests, the T4 is between 5.4 to 7 times faster than the T2+. It seems clear that the SPARC T4 processor has gone a long way filling the gap in single-thread performance, without sacrifying the multi-threaded capability as it still shows a very impressive scaling on heavy-duty multi-threaded jobs. Finally, as always at Oracle ISV Engineering, we are happy to help our ISV partners test their own applications on our platforms, so don't hesitate to contact us and let's see what the SPARC T4-based systems can do for your application! "As describe in this benchmark, Talend Enterprise Data Integration has overperformed on T4. I was generally happy to see that the T4 gave scaling opportunities for many scenarios like complex aggregations. Row by row insertion in Oracle DB is faster with more than 650,000 rows per seconds without using any bulk Oracle capabilities !" Cedric Carbone, Talend CTO.

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  • socket operation on nonsocket or bad file descriptor

    - by Magn3s1um
    I'm writing a pthread server which takes requests from clients and sends them back a bunch of .ppm files. Everything seems to go well, but sometimes when I have just 1 client connected, when trying to read from the file descriptor (for the file), it says Bad file Descriptor. This doesn't make sense, since my int fd isn't -1, and the file most certainly exists. Other times, I get this "Socket operation on nonsocket" error. This is weird because other times, it doesn't give me this error and everything works fine. When trying to connect multiple clients, for some reason, it will only send correctly to one, and then the other client gets the bad file descriptor or "nonsocket" error, even though both threads are processing the same messages and do the same routines. Anyone have an idea why? Here's the code that is giving me that error: while(mqueue.head != mqueue.tail && count < dis_m){ printf("Sending to client %s: %s\n", pointer->id, pointer->message); int fd; fd = open(pointer->message, O_RDONLY); char buf[58368]; int bytesRead; printf("This is fd %d\n", fd); bytesRead=read(fd,buf,58368); send(pointer->socket,buf,bytesRead,0); perror("Error:\n"); fflush(stdout); close(fd); mqueue.mcount--; mqueue.head = mqueue.head->next; free(pointer->message); free(pointer); pointer = mqueue.head; count++; } printf("Sending %s\n", pointer->message); int fd; fd = open(pointer->message, O_RDONLY); printf("This is fd %d\n", fd); printf("I am hhere2\n"); char buf[58368]; int bytesRead; bytesRead=read(fd,buf,58368); send(pointer->socket,buf,bytesRead,0); perror("Error:\n"); close(fd); mqueue.mcount--; if(mqueue.head != mqueue.tail){ mqueue.head = mqueue.head->next; } else{ mqueue.head->next = malloc(sizeof(struct message)); mqueue.head = mqueue.head->next; mqueue.head->next = malloc(sizeof(struct message)); mqueue.tail = mqueue.head->next; mqueue.head->message = NULL; } free(pointer->message); free(pointer); pthread_mutex_unlock(&numm); pthread_mutex_unlock(&circ); pthread_mutex_unlock(&slots); The messages for both threads are the same, being of the form ./path/imageXX.ppm where XX is the number that should go to the client. The file size of each image is 58368 bytes. Sometimes, this code hangs on the read, and stops execution. I don't know this would be either, because the file descriptor comes back as valid. Thanks in advanced. Edit: Here's some sample output: Sending to client a: ./support/images/sw90.ppm This is fd 4 Error: : Socket operation on non-socket Sending to client a: ./support/images/sw91.ppm This is fd 4 Error: : Socket operation on non-socket Sending ./support/images/sw92.ppm This is fd 4 I am hhere2 Error: : Socket operation on non-socket My dispatcher has defeated evil Sample with 2 clients (client b was serviced first) Sending to client b: ./support/images/sw87.ppm This is fd 6 Error: : Success Sending to client b: ./support/images/sw88.ppm This is fd 6 Error: : Success Sending to client b: ./support/images/sw89.ppm This is fd 6 Error: : Success This is fd 6 Error: : Bad file descriptor Sending to client a: ./support/images/sw85.ppm This is fd 6 Error: As you can see, who ever is serviced first in this instance can open the files, but not the 2nd person. Edit2: Full code. Sorry, its pretty long and terribly formatted. #include <netinet/in.h> #include <netinet/in.h> #include <netdb.h> #include <arpa/inet.h> #include <sys/types.h> #include <sys/socket.h> #include <errno.h> #include <stdio.h> #include <unistd.h> #include <pthread.h> #include <stdlib.h> #include <string.h> #include <sys/types.h> #include <sys/stat.h> #include <fcntl.h> #include "ring.h" /* Version 1 Here is what is implemented so far: The threads are created from the arguments specified (number of threads that is) The server will lock and update variables based on how many clients are in the system and such. The socket that is opened when a new client connects, must be passed to the threads. To do this, we need some sort of global array. I did this by specifying an int client and main_pool_busy, and two pointers poolsockets and nonpoolsockets. My thinking on this was that when a new client enters the system, the server thread increments the variable client. When a thread is finished with this client (after it sends it the data), the thread will decrement client and close the socket. HTTP servers act this way sometimes (they terminate the socket as soon as one transmission is sent). *Note down at bottom After the server portion increments the client counter, we must open up a new socket (denoted by new_sd) and get this value to the appropriate thread. To do this, I created global array poolsockets, which will hold all the socket descriptors for our pooled threads. The server portion gets the new socket descriptor, and places the value in the first spot of the array that has a 0. We only place a value in this array IF: 1. The variable main_pool_busy < worknum (If we have more clients in the system than in our pool, it doesn't mean we should always create a new thread. At the end of this, the server signals on the condition variable clientin that a new client has arrived. In our pooled thread, we then must walk this array and check the array until we hit our first non-zero value. This is the socket we will give to that thread. The thread then changes the array to have a zero here. What if our all threads in our pool our busy? If this is the case, then we will know it because our threads in this pool will increment main_pool_busy by one when they are working on a request and decrement it when they are done. If main_pool_busy >= worknum, then we must dynamically create a new thread. Then, we must realloc the size of our nonpoolsockets array by 1 int. We then add the new socket descriptor to our pool. Here's what we need to figure out: NOTE* Each worker should generate 100 messages which specify the worker thread ID, client socket descriptor and a copy of the client message. Additionally, each message should include a message number, starting from 0 and incrementing for each subsequent message sent to the same client. I don't know how to keep track of how many messages were to the same client. Maybe we shouldn't close the socket descriptor, but rather keep an array of structs for each socket that includes how many messages they have been sent. Then, the server adds the struct, the threads remove it, then the threads add it back once they've serviced one request (unless the count is 100). ------------------------------------------------------------- CHANGES Version 1 ---------- NONE: this is the first version. */ #define MAXSLOTS 30 #define dis_m 15 //problems with dis_m ==1 //Function prototypes void inc_clients(); void init_mutex_stuff(pthread_t*, pthread_t*); void *threadpool(void *); void server(int); void add_to_socket_pool(int); void inc_busy(); void dec_busy(); void *dispatcher(); void create_message(long, int, int, char *, char *); void init_ring(); void add_to_ring(char *, char *, int, int, int); int socket_from_string(char *); void add_to_head(char *); void add_to_tail(char *); struct message * reorder(struct message *, struct message *, int); int get_threadid(char *); void delete_socket_messages(int); struct message * merge(struct message *, struct message *, int); int get_request(char *, char *, char*); ///////////////////// //Global mutexes and condition variables pthread_mutex_t startservice; pthread_mutex_t numclients; pthread_mutex_t pool_sockets; pthread_mutex_t nonpool_sockets; pthread_mutex_t m_pool_busy; pthread_mutex_t slots; pthread_mutex_t numm; pthread_mutex_t circ; pthread_cond_t clientin; pthread_cond_t m; /////////////////////////////////////// //Global variables int clients; int main_pool_busy; int * poolsockets, nonpoolsockets; int worknum; struct ring mqueue; /////////////////////////////////////// int main(int argc, char ** argv){ //error handling if not enough arguments to program if(argc != 3){ printf("Not enough arguments to server: ./server portnum NumThreadsinPool\n"); _exit(-1); } //Convert arguments from strings to integer values int port = atoi(argv[1]); worknum = atoi(argv[2]); //Start server portion server(port); } /////////////////////////////////////////////////////////////////////////////////////////////// //The listen server thread///////////////////////////////////////////////////////////////////// /////////////////////////////////////////////////////////////////////////////////////////////// void server(int port){ int sd, new_sd; struct sockaddr_in name, cli_name; int sock_opt_val = 1; int cli_len; pthread_t threads[worknum]; //create our pthread id array pthread_t dis[1]; //create our dispatcher array (necessary to create thread) init_mutex_stuff(threads, dis); //initialize mutexes and stuff //Server setup /////////////////////////////////////////////////////// if ((sd = socket (AF_INET, SOCK_STREAM, 0)) < 0) { perror("(servConn): socket() error"); _exit (-1); } if (setsockopt (sd, SOL_SOCKET, SO_REUSEADDR, (char *) &sock_opt_val, sizeof(sock_opt_val)) < 0) { perror ("(servConn): Failed to set SO_REUSEADDR on INET socket"); _exit (-1); } name.sin_family = AF_INET; name.sin_port = htons (port); name.sin_addr.s_addr = htonl(INADDR_ANY); if (bind (sd, (struct sockaddr *)&name, sizeof(name)) < 0) { perror ("(servConn): bind() error"); _exit (-1); } listen (sd, 5); //End of server Setup ////////////////////////////////////////////////// for (;;) { cli_len = sizeof (cli_name); new_sd = accept (sd, (struct sockaddr *) &cli_name, &cli_len); printf ("Assigning new socket descriptor: %d\n", new_sd); inc_clients(); //New client has come in, increment clients add_to_socket_pool(new_sd); //Add client to the pool of sockets if (new_sd < 0) { perror ("(servConn): accept() error"); _exit (-1); } } pthread_exit(NULL); //Quit } //Adds the new socket to the array designated for pthreads in the pool void add_to_socket_pool(int socket){ pthread_mutex_lock(&m_pool_busy); //Lock so that we can check main_pool_busy int i; //If not all our main pool is busy, then allocate to one of them if(main_pool_busy < worknum){ pthread_mutex_unlock(&m_pool_busy); //unlock busy, we no longer need to hold it pthread_mutex_lock(&pool_sockets); //Lock the socket pool array so that we can edit it without worry for(i = 0; i < worknum; i++){ //Find a poolsocket that is -1; then we should put the real socket there. This value will be changed back to -1 when the thread grabs the sockfd if(poolsockets[i] == -1){ poolsockets[i] = socket; pthread_mutex_unlock(&pool_sockets); //unlock our pool array, we don't need it anymore inc_busy(); //Incrememnt busy (locks the mutex itself) pthread_cond_signal(&clientin); //Signal first thread waiting on a client that a client needs to be serviced break; } } } else{ //Dynamic thread creation goes here pthread_mutex_unlock(&m_pool_busy); } } //Increments the client number. If client number goes over worknum, we must dynamically create new pthreads void inc_clients(){ pthread_mutex_lock(&numclients); clients++; pthread_mutex_unlock(&numclients); } //Increments busy void inc_busy(){ pthread_mutex_lock(&m_pool_busy); main_pool_busy++; pthread_mutex_unlock(&m_pool_busy); } //Initialize all of our mutexes at the beginning and create our pthreads void init_mutex_stuff(pthread_t * threads, pthread_t * dis){ pthread_mutex_init(&startservice, NULL); pthread_mutex_init(&numclients, NULL); pthread_mutex_init(&pool_sockets, NULL); pthread_mutex_init(&nonpool_sockets, NULL); pthread_mutex_init(&m_pool_busy, NULL); pthread_mutex_init(&circ, NULL); pthread_cond_init (&clientin, NULL); main_pool_busy = 0; poolsockets = malloc(sizeof(int)*worknum); int threadreturn; //error checking variables long i = 0; //Loop and create pthreads for(i; i < worknum; i++){ threadreturn = pthread_create(&threads[i], NULL, threadpool, (void *) i); poolsockets[i] = -1; if(threadreturn){ perror("Thread pool created unsuccessfully"); _exit(-1); } } pthread_create(&dis[0], NULL, dispatcher, NULL); } ////////////////////////////////////////////////////////////////////////////////////////// /////////Main pool routines ///////////////////////////////////////////////////////////////////////////////////////// void dec_busy(){ pthread_mutex_lock(&m_pool_busy); main_pool_busy--; pthread_mutex_unlock(&m_pool_busy); } void dec_clients(){ pthread_mutex_lock(&numclients); clients--; pthread_mutex_unlock(&numclients); } //This is what our threadpool pthreads will be running. void *threadpool(void * threadid){ long id = (long) threadid; //Id of this thread int i; int socket; int counter = 0; //Try and gain access to the next client that comes in and wait until server signals that a client as arrived while(1){ pthread_mutex_lock(&startservice); //lock start service (required for cond wait) pthread_cond_wait(&clientin, &startservice); //wait for signal from server that client exists pthread_mutex_unlock(&startservice); //unlock mutex. pthread_mutex_lock(&pool_sockets); //Lock the pool socket so we can get the socket fd unhindered/interrupted for(i = 0; i < worknum; i++){ if(poolsockets[i] != -1){ socket = poolsockets[i]; poolsockets[i] = -1; pthread_mutex_unlock(&pool_sockets); } } printf("Thread #%d is past getting the socket\n", id); int incoming = 1; while(counter < 100 && incoming != 0){ char buffer[512]; bzero(buffer,512); int startcounter = 0; incoming = read(socket, buffer, 512); if(buffer[0] != 0){ //client ID:priority:request:arguments char id[100]; long prior; char request[100]; char arg1[100]; char message[100]; char arg2[100]; char * point; point = strtok(buffer, ":"); strcpy(id, point); point = strtok(NULL, ":"); prior = atoi(point); point = strtok(NULL, ":"); strcpy(request, point); point = strtok(NULL, ":"); strcpy(arg1, point); point = strtok(NULL, ":"); if(point != NULL){ strcpy(arg2, point); } int fd; if(strcmp(request, "start_movie") == 0){ int count = 1; while(count <= 100){ char temp[10]; snprintf(temp, 50, "%d\0", count); strcpy(message, "./support/images/"); strcat(message, arg1); strcat(message, temp); strcat(message, ".ppm"); printf("This is message %s to %s\n", message, id); count++; add_to_ring(message, id, prior, counter, socket); //Adds our created message to the ring counter++; } printf("I'm out of the loop\n"); } else if(strcmp(request, "seek_movie") == 0){ int count = atoi(arg2); while(count <= 100){ char temp[10]; snprintf(temp, 10, "%d\0", count); strcpy(message, "./support/images/"); strcat(message, arg1); strcat(message, temp); strcat(message, ".ppm"); printf("This is message %s\n", message); count++; } } //create_message(id, socket, counter, buffer, message); //Creates our message from the input from the client. Stores it in buffer } else{ delete_socket_messages(socket); break; } } counter = 0; close(socket);//Zero out counter again } dec_clients(); //client serviced, decrement clients dec_busy(); //thread finished, decrement busy } //Creates a message void create_message(long threadid, int socket, int counter, char * buffer, char * message){ snprintf(message, strlen(buffer)+15, "%d:%d:%d:%s", threadid, socket, counter, buffer); } //Gets the socket from the message string (maybe I should just pass in the socket to another method) int socket_from_string(char * message){ char * substr1 = strstr(message, ":"); char * substr2 = substr1; substr2++; int occurance = strcspn(substr2, ":"); char sock[10]; strncpy(sock, substr2, occurance); return atoi(sock); } //Adds message to our ring buffer's head void add_to_head(char * message){ printf("Adding to head of ring\n"); mqueue.head->message = malloc(strlen(message)+1); //Allocate space for message strcpy(mqueue.head->message, message); //copy bytes into allocated space } //Adds our message to our ring buffer's tail void add_to_tail(char * message){ printf("Adding to tail of ring\n"); mqueue.tail->message = malloc(strlen(message)+1); //allocate space for message strcpy(mqueue.tail->message, message); //copy bytes into allocated space mqueue.tail->next = malloc(sizeof(struct message)); //allocate space for the next message struct } //Adds a message to our ring void add_to_ring(char * message, char * id, int prior, int mnum, int socket){ //printf("This is message %s:" , message); pthread_mutex_lock(&circ); //Lock the ring buffer pthread_mutex_lock(&numm); //Lock the message count (will need this to make sure we can't fill the buffer over the max slots) if(mqueue.head->message == NULL){ add_to_head(message); //Adds it to head mqueue.head->socket = socket; //Set message socket mqueue.head->priority = prior; //Set its priority (thread id) mqueue.head->mnum = mnum; //Set its message number (used for sorting) mqueue.head->id = malloc(sizeof(id)); strcpy(mqueue.head->id, id); } else if(mqueue.tail->message == NULL){ //This is the problem for dis_m 1 I'm pretty sure add_to_tail(message); mqueue.tail->socket = socket; mqueue.tail->priority = prior; mqueue.tail->mnum = mnum; mqueue.tail->id = malloc(sizeof(id)); strcpy(mqueue.tail->id, id); } else{ mqueue.tail->next = malloc(sizeof(struct message)); mqueue.tail = mqueue.tail->next; add_to_tail(message); mqueue.tail->socket = socket; mqueue.tail->priority = prior; mqueue.tail->mnum = mnum; mqueue.tail->id = malloc(sizeof(id)); strcpy(mqueue.tail->id, id); } mqueue.mcount++; pthread_mutex_unlock(&circ); if(mqueue.mcount >= dis_m){ pthread_mutex_unlock(&numm); pthread_cond_signal(&m); } else{ pthread_mutex_unlock(&numm); } printf("out of add to ring\n"); fflush(stdout); } ////////////////////////////////// //Dispatcher routines ///////////////////////////////// void *dispatcher(){ init_ring(); while(1){ pthread_mutex_lock(&slots); pthread_cond_wait(&m, &slots); pthread_mutex_lock(&numm); pthread_mutex_lock(&circ); printf("Dispatcher to the rescue!\n"); mqueue.head = reorder(mqueue.head, mqueue.tail, mqueue.mcount); //printf("This is the head %s\n", mqueue.head->message); //printf("This is the tail %s\n", mqueue.head->message); fflush(stdout); struct message * pointer = mqueue.head; int count = 0; while(mqueue.head != mqueue.tail && count < dis_m){ printf("Sending to client %s: %s\n", pointer->id, pointer->message); int fd; fd = open(pointer->message, O_RDONLY); char buf[58368]; int bytesRead; printf("This is fd %d\n", fd); bytesRead=read(fd,buf,58368); send(pointer->socket,buf,bytesRead,0); perror("Error:\n"); fflush(stdout); close(fd); mqueue.mcount--; mqueue.head = mqueue.head->next; free(pointer->message); free(pointer); pointer = mqueue.head; count++; } printf("Sending %s\n", pointer->message); int fd; fd = open(pointer->message, O_RDONLY); printf("This is fd %d\n", fd); printf("I am hhere2\n"); char buf[58368]; int bytesRead; bytesRead=read(fd,buf,58368); send(pointer->socket,buf,bytesRead,0); perror("Error:\n"); close(fd); mqueue.mcount--; if(mqueue.head != mqueue.tail){ mqueue.head = mqueue.head->next; } else{ mqueue.head->next = malloc(sizeof(struct message)); mqueue.head = mqueue.head->next; mqueue.head->next = malloc(sizeof(struct message)); mqueue.tail = mqueue.head->next; mqueue.head->message = NULL; } free(pointer->message); free(pointer); pthread_mutex_unlock(&numm); pthread_mutex_unlock(&circ); pthread_mutex_unlock(&slots); printf("My dispatcher has defeated evil\n"); } } void init_ring(){ mqueue.head = malloc(sizeof(struct message)); mqueue.head->next = malloc(sizeof(struct message)); mqueue.tail = mqueue.head->next; mqueue.mcount = 0; } struct message * reorder(struct message * begin, struct message * end, int num){ //printf("I am reordering for size %d\n", num); fflush(stdout); int i; if(num == 1){ //printf("Begin: %s\n", begin->message); begin->next = NULL; return begin; } else{ struct message * left = begin; struct message * right; int middle = num/2; for(i = 1; i < middle; i++){ left = left->next; } right = left -> next; left -> next = NULL; //printf("Begin: %s\nLeft: %s\nright: %s\nend:%s\n", begin->message, left->message, right->message, end->message); left = reorder(begin, left, middle); if(num%2 != 0){ right = reorder(right, end, middle+1); } else{ right = reorder(right, end, middle); } return merge(left, right, num); } } struct message * merge(struct message * left, struct message * right, int num){ //printf("I am merginging! left: %s %d, right: %s %dnum: %d\n", left->message,left->priority, right->message, right->priority, num); struct message * start, * point; int lenL= 0; int lenR = 0; int flagL = 0; int flagR = 0; int count = 0; int middle1 = num/2; int middle2; if(num%2 != 0){ middle2 = middle1+1; } else{ middle2 = middle1; } while(lenL < middle1 && lenR < middle2){ count++; //printf("In here for count %d\n", count); if(lenL == 0 && lenR == 0){ if(left->priority < right->priority){ start = left; //Set the start point point = left; //set our enum; left = left->next; //move the left pointer point->next = NULL; //Set the next node to NULL lenL++; } else if(left->priority > right->priority){ start = right; point = right; right = right->next; point->next = NULL; lenR++; } else{ if(left->mnum < right->mnum){ ////printf("This is where we are\n"); start = left; //Set the start point point = left; //set our enum; left = left->next; //move the left pointer point->next = NULL; //Set the next node to NULL lenL++; } else{ start = right; point = right; right = right->next; point->next = NULL; lenR++; } } } else{ if(left->priority < right->priority){ point->next = left; left = left->next; //move the left pointer point = point->next; point->next = NULL; //Set the next node to NULL lenL++; } else if(left->priority > right->priority){ point->next = right; right = right->next; point = point->next; point->next = NULL; lenR++; } else{ if(left->mnum < right->mnum){ point->next = left; //set our enum; left = left->next; point = point->next;//move the left pointer point->next = NULL; //Set the next node to NULL lenL++; } else{ point->next = right; right = right->next; point = point->next; point->next = NULL; lenR++; } } } if(lenL == middle1){ flagL = 1; break; } if(lenR == middle2){ flagR = 1; break; } } if(flagL == 1){ point->next = right; point = point->next; for(lenR; lenR< middle2-1; lenR++){ point = point->next; } point->next = NULL; mqueue.tail = point; } else{ point->next = left; point = point->next; for(lenL; lenL< middle1-1; lenL++){ point = point->next; } point->next = NULL; mqueue.tail = point; } //printf("This is the start %s\n", start->message); //printf("This is mqueue.tail %s\n", mqueue.tail->message); return start; } void delete_socket_messages(int a){ }

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  • What are the relative merits for implementing an Erlang-style "Continuation" pattern in C#

    - by JoeGeeky
    What are the relative merits (or demerits) for implementing an Erlang-style "Continuation" pattern in C#. I'm working on a project that has a large number of Lowest priority threads and I'm wondering if my approach may be all wrong. It would seem there is a reasonable upper limit to the number of long-running threads that any one Process 'should' spawn. With that said, I'm not sure what would signal the tipping-point for too many thread or when alternate patterns such as "Continuation" would be more suitable. In this case, many of the threads do a small amount of work and then sleep until woken to go again (Ex. Heartbeat, purge caches, etc...). This continues for the life of the Process.

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  • A Basic Thread

    - by Joe Mayo
    Most of the programs written are single-threaded, meaning that they run on the main execution thread. For various reasons such as performance, scalability, and/or responsiveness additional threads can be useful. .NET has extensive threading support, from the basic threads introduced in v1.0 to the Task Parallel Library (TPL) introduced in v4.0. To get started with threads, it's helpful to begin with the basics; starting a Thread. Why Do I Care? The scenario I'll use for needing to use a thread is writing to a file.  Sometimes, writing to a file takes a while and you don't want your user interface to lock up until the file write is done. In other words, you want the application to be responsive to the user. How Would I Go About It? The solution is to launch a new thread that performs the file write, allowing the main thread to return to the user right away.  Whenever the file writing thread completes, it will let the user know.  In the meantime, the user is free to interact with the program for other tasks. The following examples demonstrate how to do this. Show Me the Code? The code we'll use to work with threads is in the System.Threading namespace, so you'll need the following using directive at the top of the file: using System.Threading; When you run code on a thread, the code is specified via a method.  Here's the code that will execute on the thread: private static void WriteFile() { Thread.Sleep(1000); Console.WriteLine("File Written."); } The call to Thread.Sleep(1000) delays thread execution. The parameter is specified in milliseconds, and 1000 means that this will cause the program to sleep for approximately 1 second.  This method happens to be static, but that's just part of this example, which you'll see is launched from the static Main method.  A thread could be instance or static.  Notice that the method does not have parameters and does not have a return type. As you know, the way to refer to a method is via a delegate.  There is a delegate named ThreadStart in System.Threading that refers to a method without parameters or return type, shown below: ThreadStart fileWriterHandlerDelegate = new ThreadStart(WriteFile); I'll show you the whole program below, but the ThreadStart instance above goes in the Main method. The thread uses the ThreadStart instance, fileWriterHandlerDelegate, to specify the method to execute on the thread: Thread fileWriter = new Thread(fileWriterHandlerDelegate); As shown above, the argument type for the Thread constructor is the ThreadStart delegate type. The fileWriterHandlerDelegate argument is an instance of the ThreadStart delegate type. This creates an instance of a thread and what code will execute, but the new thread instance, fileWriter, isn't running yet. You have to explicitly start it, like this: fileWriter.Start(); Now, the code in the WriteFile method is executing on a separate thread. Meanwhile, the main thread that started the fileWriter thread continues on it's own.  You have two threads running at the same time. Okay, I'm Starting to Get Glassy Eyed. How Does it All Fit Together? The example below is the whole program, pulling all the previous bits together. It's followed by its output and an explanation. using System; using System.Threading; namespace BasicThread { class Program { static void Main() { ThreadStart fileWriterHandlerDelegate = new ThreadStart(WriteFile); Thread fileWriter = new Thread(fileWriterHandlerDelegate); Console.WriteLine("Starting FileWriter"); fileWriter.Start(); Console.WriteLine("Called FileWriter"); Console.ReadKey(); } private static void WriteFile() { Thread.Sleep(1000); Console.WriteLine("File Written"); } } } And here's the output: Starting FileWriter Called FileWriter File Written So, Why are the Printouts Backwards? The output above corresponds to Console.Writeline statements in the program, with the second and third seemingly reversed. In a single-threaded program, "File Written" would print before "Called FileWriter". However, this is a multi-threaded (2 or more threads) program.  In multi-threading, you can't make any assumptions about when a given thread will run.  In this case, I added the Sleep statement to the WriteFile method to greatly increase the chances that the message from the main thread will print first. Without the Thread.Sleep, you could run this on a system with multiple cores and/or multiple processors and potentially get different results each time. Interesting Tangent but What Should I Get Out of All This? Going back to the main point, launching the WriteFile method on a separate thread made the program more responsive.  The file writing logic ran for a while, but the main thread returned to the user, as demonstrated by the print out of "Called FileWriter".  When the file write finished, it let the user know via another print statement. This was a very efficient use of CPU resources that made for a more pleasant user experience. Joe

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  • Graphic card for parallel programming vs traditional methods

    - by Sambatyon
    With a simple search in amazon one can see that the modern approach for parallel programming is to use your graphic card. However I am still a little bit skeptical about it. My last computer has an 8 core CPU which I need is enough for basic all my parallel needs, if I need more I will probably use MPI through a network using my old machines. All in all, Why and/or when should I use CUDA or another method which uses my graphic card instead of traditional methods like pthreads, java threads, boost threads or the new C++ 11 threads? What about using processes?

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  • Concurrency Utilities for Java EE Early Draft (JSR 236)

    - by arungupta
    Concurrency Utilities for Java EE is being worked as JSR 236 and has released an Early Draft. It provides concurrency capabilities to Java EE application components without compromising container integrity. Simple (common) and advanced concurrency patterns are easily supported without sacrificing usability. Using Java SE concurrency utilities such as java.util.concurrent API, java.lang.Thread and java.util.Timer in a Java EE application component such as EJB or Servlet are problematic since the container and server have no knowledge of these resources. JSR 236 enables concurrency largely by extending the Concurrency Utilities API developed under JSR-166. This also allows a consistency between Java SE and Java EE concurrency programming model. There are four main programming interfaces available: ManagedExecutorService ManagedScheduledExecutorService ContextService ManagedThreadFactory ManagedExecutorService is a managed version of java.util.concurrent.ExecutorService. The implementations of this interface are provided by the container and accessible using JNDI reference: <resource-env-ref>  <resource-env-ref-name>    concurrent/BatchExecutor  </resource-env-ref-name>  <resource-env-ref-type>    javax.enterprise.concurrent.ManagedExecutorService  </resource-env-ref-type><resource-env-ref> and available as: @Resource(name="concurrent/BatchExecutor")ManagedExecutorService executor; Its recommended to bind the JNDI references in the java:comp/env/concurrent subcontext. The asynchronous tasks that need to be executed need to implement java.lang.Runnable or java.util.concurrent.Callable interface as: public class MyTask implements Runnable { public void run() { // business logic goes here }} OR public class MyTask2 implements Callable<Date> {  public Date call() { // business logic goes here   }} The task is then submitted to the executor using one of the submit method that return a Future instance. The Future represents the result of the task and can also be used to check if the task is complete or wait for its completion. Future<String> future = executor.submit(new MyTask(), String.class);. . .String result = future.get(); Another example to submit tasks is: class MyTask implements Callback<Long> { . . . }class MyTask2 implements Callback<Date> { . . . }ArrayList<Callable> tasks = new ArrayList<();tasks.add(new MyTask());tasks.add(new MyTask2());List<Future<Object>> result = executor.invokeAll(tasks); The ManagedExecutorService may be configured for different properties such as: Hung Task Threshold: Time in milliseconds that a task can execute before it is considered hung Pool Info Core Size: Number of threads to keep alive Maximum Size: Maximum number of threads allowed in the pool Keep Alive: Time to allow threads to remain idle when # of threads > Core Size Work Queue Capacity: # of tasks that can be stored in inbound buffer Thread Use: Application intend to run short vs long-running tasks, accordingly pooled or daemon threads are picked ManagedScheduledExecutorService adds delay and periodic task running capabilities to ManagedExecutorService. The implementations of this interface are provided by the container and accessible using JNDI reference: <resource-env-ref>  <resource-env-ref-name>    concurrent/BatchExecutor  </resource-env-ref-name>  <resource-env-ref-type>    javax.enterprise.concurrent.ManagedExecutorService  </resource-env-ref-type><resource-env-ref> and available as: @Resource(name="concurrent/timedExecutor")ManagedExecutorService executor; And then the tasks are submitted using submit, invokeXXX or scheduleXXX methods. ScheduledFuture<?> future = executor.schedule(new MyTask(), 5, TimeUnit.SECONDS); This will create and execute a one-shot action that becomes enabled after 5 seconds of delay. More control is possible using one of the newly added methods: MyTaskListener implements ManagedTaskListener {  public void taskStarting(...) { . . . }  public void taskSubmitted(...) { . . . }  public void taskDone(...) { . . . }  public void taskAborted(...) { . . . } }ScheduledFuture<?> future = executor.schedule(new MyTask(), 5, TimeUnit.SECONDS, new MyTaskListener()); Here, ManagedTaskListener is used to monitor the state of a task's future. ManagedThreadFactory provides a method for creating threads for execution in a managed environment. A simple usage is: @Resource(name="concurrent/myThreadFactory")ManagedThreadFactory factory;. . .Thread thread = factory.newThread(new Runnable() { . . . }); concurrent/myThreadFactory is a JNDI resource. There is lot of interesting content in the Early Draft, download it, and read yourself. The implementation will be made available soon and also be integrated in GlassFish 4 as well. Some references for further exploring ... Javadoc Early Draft Specification concurrency-ee-spec.java.net [email protected]

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  • Disqus thread migration. Gotchas?

    - by sramsay
    I've been migrating a site to a new domain. The site itself is pretty straightforward (it uses Jekyll), and everything has gone fine -- except migration of Disqus threads. I've had partial success -- some of the threads have migrated successfully, but not all. I've tried the domain migration wizard (which caught a few), the URL mapper (which caught a few), and the 301 redirect crawler (which caught a few). But the remaining threads just won't move, no matter which method I use. So, I suppose I suppose I'm asking if there are any "gotchas" I should know about with this. When you execute any of these migration tools, it says it will "take awhile." Does that mean hours? Days? I can't tell if it's working, and there's no logging or error reporting that I can see.

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  • Threading iPhone

    - by bobobobo
    Say I have a group of large meshes that I have to intersect rays against. Assume also, for whatever reason, I cannot further simplify/reduce poly check count by spatial subdivisioning. I can do this in parallel: bool intersects( list of meshes ) // a mesh is a group of triangles { create n threads foreach mesh in meshes assign to a thread in threads wait until ( threads.run() ) ; // run asynchronously // when they're all done // pull out intersected triangles // from per-thread context data } Can you do this in ios for games? Or is the overhead of thread creation and mutex waiting going to beat-out the benefit of multithreading?

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  • Thread count in Java game

    - by Taylor Hill
    I'm just curious as to what a reasonable number of threads is for a simple 2D mmo in Java. Is it reasonable to have two threads per connection, one for the input stream and one for the output stream? The reason I ask is because I use a blocking method on the input stream, and a workaround seems unnecessarily complex if I were to try to get around it without adding threads. This is mostly for my own edification; I don't expect to have 5 million people playing it ever, or even 5, but I'm wondering what a good scalable solution is, and if this is reasonable for a small server (<30 connections).

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  • Scalability of multi-threading in game server

    - by Taylor Hill
    What is a reasonable number of threads for a simple 2D mmo in Java? Is it reasonable to have two threads per connection, one for the input stream and one for the output stream? The reason I ask is because I use a blocking method on the input stream, and a workaround seems unnecessarily complex if I were to try to get around it without adding threads. This is mostly for my own edification; I don't expect to have 5 million people playing it ever, or even 5, but I'm wondering what a good scalable solution is, and if this is reasonable for a small server (<30 connections).

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  • The CLR has been unable to transition from COM context [...] for 60 seconds

    - by BlueRaja The Green Unicorn
    I am getting this error on code that used to work. I have not changed the code. Here is the full error: The CLR has been unable to transition from COM context 0x3322d98 to COM context 0x3322f08 for 60 seconds. The thread that owns the destination context/apartment is most likely either doing a non pumping wait or processing a very long running operation without pumping Windows messages. This situation generally has a negative performance impact and may even lead to the application becoming non responsive or memory usage accumulating continually over time. To avoid this problem, all single threaded apartment (STA) threads should use pumping wait primitives (such as CoWaitForMultipleHandles) and routinely pump messages during long running operations. And here is the code that caused it: var openFileDialog1 = new System.Windows.Forms.OpenFileDialog(); openFileDialog1.DefaultExt = "mdb"; openFileDialog1.Filter = "Management Database (manage.mdb)|manage.mdb"; //Stalls indefinitely on the following line, then gives the CLR error //one minute later. The dialog never opens. if(openFileDialog1.ShowDialog() == DialogResult.OK) { .... } Yes, I am sure the dialog is not open in the background, and no, I don't have any explicit COM code or unmanaged marshalling or multithreading. I have no idea why the OpenFileDialog won't open - any ideas?

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  • Abysmal transfer speeds on gigabit network

    - by Vegard Larsen
    I am having trouble getting my Gigabit network to work properly between my desktop computer and my Windows Home Server. When copying files to my server (connected through my switch), I am seeing file transfer speeds of below 10MB/s, sometimes even below 1MB/s. The machine configurations are: Desktop Intel Core 2 Quad Q6600 Windows 7 Ultimate x64 2x WD Green 1TB drives in striped RAID 4GB RAM AB9 QuadGT motherboard Realtek RTL8810SC network adapter Windows Home Server AMD Athlon 64 X2 4GB RAM 6x WD Green 1,5TB drives in storage pool Gigabyte GA-MA78GM-S2H motherboard Realtek 8111C network adapter Switch dLink Green DGS-1008D 8-port Both machines report being connected at 1Gbps. The switch lights up with green lights for those two ports, indicating 1Gbps. When connecting the machines through the switch, I am seeing insanely low speeds from WHS to the desktop measured with iperf: 10Kbits/sec (WHS is running iperf -c, desktop is iperf -s). Using iperf the other way (WHS is iperf -s, desktop iperf -c) speeds are also bad (~20Mbits/sec). Connecting the machines directly with a patch cable, I see much higher speeds when connecting from desktop to WHS (~300 Mbits/sec), but still around 10Kbits/sec when connecting from WHS to the desktop. File transfer speeds are also much quicker (both directions). Log from desktop for iperf connection from WHS (through switch): C:\temp>iperf -s ------------------------------------------------------------ Server listening on TCP port 5001 TCP window size: 8.00 KByte (default) ------------------------------------------------------------ [248] local 192.168.1.32 port 5001 connected with 192.168.1.20 port 3227 [ ID] Interval Transfer Bandwidth [248] 0.0-18.5 sec 24.0 KBytes 10.6 Kbits/sec Log from desktop for iperf connection to WHS (through switch): C:\temp>iperf -c 192.168.1.20 ------------------------------------------------------------ Client connecting to 192.168.1.20, TCP port 5001 TCP window size: 8.00 KByte (default) ------------------------------------------------------------ [148] local 192.168.1.32 port 57012 connected with 192.168.1.20 port 5001 [ ID] Interval Transfer Bandwidth [148] 0.0-10.3 sec 28.5 MBytes 23.3 Mbits/sec What is going on here? Unfortunately I don't have any other gigabit-capable devices to try with.

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  • CentOS vps is randomly rebooting

    - by develroot
    I have a centos vps (Parallels Virtuozzo container) which has been running for months. However, a few days ago it started to randomly reboot itself, and i can't find out why. And the biggest problem that i don't understand is that it takes 40 minutes to reboot (as far as i can see in the logs) root ~ # cat /var/log/messages | grep shutdown Oct 11 13:52:11 vps27 shutdown[23968]: shutting down for system halt Oct 14 14:55:17 vps27 shutdown[30662]: shutting down for system halt Oct 15 06:21:23 vps27 shutdown[20157]: shutting down for system halt And notice the time difference between shutdown and xinetd's start: Oct 15 06:21:23 vps27 shutdown[20157]: shutting down for system halt Oct 15 06:21:24 vps27 init: Switching to runlevel: 0 Oct 15 06:21:27 vps27 saslauthd[30614]: server_exit : master exited: 30614 Oct 15 06:21:38 vps27 named[30661]: shutting down Oct 15 06:21:47 vps27 exiting on signal 15 Oct 15 07:04:34 vps27 syslogd 1.4.1: restart. Oct 15 07:05:06 vps27 xinetd[1471]: xinetd Version 2.3.14 started with libwrap loadavg labeled-networking options compiled in. Oct 15 07:05:06 vps27 xinetd[1471]: Started working: 0 available services And here's what Parallels Power Panel says in terms of Status Changes: Time Old Status Status Obtained Oct 15, 2011 06:23:46 AM Mounted Down Oct 15, 2011 06:22:31 AM Running Mounted Oct 14, 2011 03:06:48 PM Starting Running Oct 14, 2011 03:06:23 PM Down Starting Oct 14, 2011 03:06:08 PM Mounted Down Oct 14, 2011 02:58:24 PM Running Mounted For some reason it's getting into Mounting mode and then restarts itself. The only problem that i can imagine is disk space utilization, which is now 84%. But can that be a reson for system halt? Time Category Details Type Parameter Oct 15, 2011 07:08:33 AM Resource Resource counter_disk_share_used yellow alert on environment vps27 current value: 82 soft limit: 85 hard limit: 95 Yellow zone counter_disk_share_used Oct 15, 2011 06:27:23 AM Resource Resource counter_disk_share_used yellow alert on environment vps27 current value: 82 soft limit: 85 hard limit: 95 Yellow zone counter_disk_share_used Oct 15, 2011 06:23:50 AM Resource Resource counter_disk_share_used green alert on environment vps27 current value: 0 soft limit: hard limit: 0 Green zone counter_disk_share_used Oct 14, 2011 03:06:24 PM Resource Resource counter_disk_share_used yellow alert on environment vps27 current value: 83 soft limit: 85 hard limit: 95 Yellow zone counter_disk_share_used Oct 14, 2011 03:05:50 PM Resource Resource counter_disk_share_used green alert on environment vps27 current value: 0 soft limit: hard limit: 0 Green zone counter_disk_share_used

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  • Metro: Introduction to CSS 3 Grid Layout

    - by Stephen.Walther
    The purpose of this blog post is to provide you with a quick introduction to the new W3C CSS 3 Grid Layout standard. You can use CSS Grid Layout in Metro style applications written with JavaScript to lay out the content of an HTML page. CSS Grid Layout provides you with all of the benefits of using HTML tables for layout without requiring you to actually use any HTML table elements. Doing Page Layouts without Tables Back in the 1990’s, if you wanted to create a fancy website, then you would use HTML tables for layout. For example, if you wanted to create a standard three-column page layout then you would create an HTML table with three columns like this: <table height="100%"> <tr> <td valign="top" width="300px" bgcolor="red"> Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column </td> <td valign="top" bgcolor="green"> Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column </td> <td valign="top" width="300px" bgcolor="blue"> Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column </td> </tr> </table> When the table above gets rendered out to a browser, you end up with the following three-column layout: The width of the left and right columns is fixed – the width of the middle column expands or contracts depending on the width of the browser. Sometime around the year 2005, everyone decided that using tables for layout was a bad idea. Instead of using tables for layout — it was collectively decided by the spirit of the Web — you should use Cascading Style Sheets instead. Why is using HTML tables for layout bad? Using tables for layout breaks the semantics of the TABLE element. A TABLE element should be used only for displaying tabular information such as train schedules or moon phases. Using tables for layout is bad for accessibility (The Web Content Accessibility Guidelines 1.0 is explicit about this) and using tables for layout is bad for separating content from layout (see http://CSSZenGarden.com). Post 2005, anyone who used HTML tables for layout were encouraged to hold their heads down in shame. That’s all well and good, but the problem with using CSS for layout is that it can be more difficult to work with CSS than HTML tables. For example, to achieve a standard three-column layout, you either need to use absolute positioning or floats. Here’s a three-column layout with floats: <style type="text/css"> #container { min-width: 800px; } #leftColumn { float: left; width: 300px; height: 100%; background-color:red; } #middleColumn { background-color:green; height: 100%; } #rightColumn { float: right; width: 300px; height: 100%; background-color:blue; } </style> <div id="container"> <div id="rightColumn"> Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column </div> <div id="leftColumn"> Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column </div> <div id="middleColumn"> Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column </div> </div> The page above contains four DIV elements: a container DIV which contains a leftColumn, middleColumn, and rightColumn DIV. The leftColumn DIV element is floated to the left and the rightColumn DIV element is floated to the right. Notice that the rightColumn DIV appears in the page before the middleColumn DIV – this unintuitive ordering is necessary to get the floats to work correctly (see http://stackoverflow.com/questions/533607/css-three-column-layout-problem). The page above (almost) works with the most recent versions of most browsers. For example, you get the correct three-column layout in both Firefox and Chrome: And the layout mostly works with Internet Explorer 9 except for the fact that for some strange reason the min-width doesn’t work so when you shrink the width of your browser, you can get the following unwanted layout: Notice how the middle column (the green column) bleeds to the left and right. People have solved these issues with more complicated CSS. For example, see: http://matthewjamestaylor.com/blog/holy-grail-no-quirks-mode.htm But, at this point, no one could argue that using CSS is easier or more intuitive than tables. It takes work to get a layout with CSS and we know that we could achieve the same layout more easily using HTML tables. Using CSS Grid Layout CSS Grid Layout is a new W3C standard which provides you with all of the benefits of using HTML tables for layout without the disadvantage of using an HTML TABLE element. In other words, CSS Grid Layout enables you to perform table layouts using pure Cascading Style Sheets. The CSS Grid Layout standard is still in a “Working Draft” state (it is not finalized) and it is located here: http://www.w3.org/TR/css3-grid-layout/ The CSS Grid Layout standard is only supported by Internet Explorer 10 and there are no signs that any browser other than Internet Explorer will support this standard in the near future. This means that it is only practical to take advantage of CSS Grid Layout when building Metro style applications with JavaScript. Here’s how you can create a standard three-column layout using a CSS Grid Layout: <!DOCTYPE html> <html> <head> <style type="text/css"> html, body, #container { height: 100%; padding: 0px; margin: 0px; } #container { display: -ms-grid; -ms-grid-columns: 300px auto 300px; -ms-grid-rows: 100%; } #leftColumn { -ms-grid-column: 1; background-color:red; } #middleColumn { -ms-grid-column: 2; background-color:green; } #rightColumn { -ms-grid-column: 3; background-color:blue; } </style> </head> <body> <div id="container"> <div id="leftColumn"> Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column </div> <div id="middleColumn"> Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column </div> <div id="rightColumn"> Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column </div> </div> </body> </html> When the page above is rendered in Internet Explorer 10, you get a standard three-column layout: The page above contains four DIV elements: a container DIV which contains a leftColumn DIV, middleColumn DIV, and rightColumn DIV. The container DIV is set to Grid display mode with the following CSS rule: #container { display: -ms-grid; -ms-grid-columns: 300px auto 300px; -ms-grid-rows: 100%; } The display property is set to the value “-ms-grid”. This property causes the container DIV to lay out its child elements in a grid. (Notice that you use “-ms-grid” instead of “grid”. The “-ms-“ prefix is used because the CSS Grid Layout standard is still preliminary. This implementation only works with IE10 and it might change before the final release.) The grid columns and rows are defined with the “-ms-grid-columns” and “-ms-grid-rows” properties. The style rule above creates a grid with three columns and one row. The left and right columns are fixed sized at 300 pixels. The middle column sizes automatically depending on the remaining space available. The leftColumn, middleColumn, and rightColumn DIVs are positioned within the container grid element with the following CSS rules: #leftColumn { -ms-grid-column: 1; background-color:red; } #middleColumn { -ms-grid-column: 2; background-color:green; } #rightColumn { -ms-grid-column: 3; background-color:blue; } The “-ms-grid-column” property is used to specify the column associated with the element selected by the style sheet selector. The leftColumn DIV is positioned in the first grid column, the middleColumn DIV is positioned in the second grid column, and the rightColumn DIV is positioned in the third grid column. I find using CSS Grid Layout to be just as intuitive as using an HTML table for layout. You define your columns and rows and then you position different elements within these columns and rows. Very straightforward. Creating Multiple Columns and Rows In the previous section, we created a super simple three-column layout. This layout contained only a single row. In this section, let’s create a slightly more complicated layout which contains more than one row: The following page contains a header row, a content row, and a footer row. The content row contains three columns: <!DOCTYPE html> <html> <head> <style type="text/css"> html, body, #container { height: 100%; padding: 0px; margin: 0px; } #container { display: -ms-grid; -ms-grid-columns: 300px auto 300px; -ms-grid-rows: 100px 1fr 100px; } #header { -ms-grid-column: 1; -ms-grid-column-span: 3; -ms-grid-row: 1; background-color: yellow; } #leftColumn { -ms-grid-column: 1; -ms-grid-row: 2; background-color:red; } #middleColumn { -ms-grid-column: 2; -ms-grid-row: 2; background-color:green; } #rightColumn { -ms-grid-column: 3; -ms-grid-row: 2; background-color:blue; } #footer { -ms-grid-column: 1; -ms-grid-column-span: 3; -ms-grid-row: 3; background-color: orange; } </style> </head> <body> <div id="container"> <div id="header"> Header, Header, Header </div> <div id="leftColumn"> Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column </div> <div id="middleColumn"> Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column </div> <div id="rightColumn"> Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column </div> <div id="footer"> Footer, Footer, Footer </div> </div> </body> </html> In the page above, the grid layout is created with the following rule which creates a grid with three rows and three columns: #container { display: -ms-grid; -ms-grid-columns: 300px auto 300px; -ms-grid-rows: 100px 1fr 100px; } The header is created with the following rule: #header { -ms-grid-column: 1; -ms-grid-column-span: 3; -ms-grid-row: 1; background-color: yellow; } The header is positioned in column 1 and row 1. Furthermore, notice that the “-ms-grid-column-span” property is used to span the header across three columns. CSS Grid Layout and Fractional Units When you use CSS Grid Layout, you can take advantage of fractional units. Fractional units provide you with an easy way of dividing up remaining space in a page. Imagine, for example, that you want to create a three-column page layout. You want the size of the first column to be fixed at 200 pixels and you want to divide the remaining space among the remaining three columns. The width of the second column is equal to the combined width of the third and fourth columns. The following CSS rule creates four columns with the desired widths: #container { display: -ms-grid; -ms-grid-columns: 200px 2fr 1fr 1fr; -ms-grid-rows: 1fr; } The fr unit represents a fraction. The grid above contains four columns. The second column is two times the size (2fr) of the third (1fr) and fourth (1fr) columns. When you use the fractional unit, the remaining space is divided up using fractional amounts. Notice that the single row is set to a height of 1fr. The single grid row gobbles up the entire vertical space. Here’s the entire HTML page: <!DOCTYPE html> <html> <head> <style type="text/css"> html, body, #container { height: 100%; padding: 0px; margin: 0px; } #container { display: -ms-grid; -ms-grid-columns: 200px 2fr 1fr 1fr; -ms-grid-rows: 1fr; } #firstColumn { -ms-grid-column: 1; background-color:red; } #secondColumn { -ms-grid-column: 2; background-color:green; } #thirdColumn { -ms-grid-column: 3; background-color:blue; } #fourthColumn { -ms-grid-column: 4; background-color:orange; } </style> </head> <body> <div id="container"> <div id="firstColumn"> First Column, First Column, First Column </div> <div id="secondColumn"> Second Column, Second Column, Second Column </div> <div id="thirdColumn"> Third Column, Third Column, Third Column </div> <div id="fourthColumn"> Fourth Column, Fourth Column, Fourth Column </div> </div> </body> </html>   Summary There is more in the CSS 3 Grid Layout standard than discussed in this blog post. My goal was to describe the basics. If you want to learn more than you can read through the entire standard at http://www.w3.org/TR/css3-grid-layout/ In this blog post, I described some of the difficulties that you might encounter when attempting to replace HTML tables with Cascading Style Sheets when laying out a web page. I explained how you can take advantage of the CSS 3 Grid Layout standard to avoid these problems when building Metro style applications using JavaScript. CSS 3 Grid Layout provides you with all of the benefits of using HTML tables for laying out a page without requiring you to use HTML table elements.

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  • Metro: Introduction to CSS 3 Grid Layout

    - by Stephen.Walther
    The purpose of this blog post is to provide you with a quick introduction to the new W3C CSS 3 Grid Layout standard. You can use CSS Grid Layout in Metro style applications written with JavaScript to lay out the content of an HTML page. CSS Grid Layout provides you with all of the benefits of using HTML tables for layout without requiring you to actually use any HTML table elements. Doing Page Layouts without Tables Back in the 1990’s, if you wanted to create a fancy website, then you would use HTML tables for layout. For example, if you wanted to create a standard three-column page layout then you would create an HTML table with three columns like this: <table height="100%"> <tr> <td valign="top" width="300px" bgcolor="red"> Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column </td> <td valign="top" bgcolor="green"> Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column </td> <td valign="top" width="300px" bgcolor="blue"> Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column </td> </tr> </table> When the table above gets rendered out to a browser, you end up with the following three-column layout: The width of the left and right columns is fixed – the width of the middle column expands or contracts depending on the width of the browser. Sometime around the year 2005, everyone decided that using tables for layout was a bad idea. Instead of using tables for layout — it was collectively decided by the spirit of the Web — you should use Cascading Style Sheets instead. Why is using HTML tables for layout bad? Using tables for layout breaks the semantics of the TABLE element. A TABLE element should be used only for displaying tabular information such as train schedules or moon phases. Using tables for layout is bad for accessibility (The Web Content Accessibility Guidelines 1.0 is explicit about this) and using tables for layout is bad for separating content from layout (see http://CSSZenGarden.com). Post 2005, anyone who used HTML tables for layout were encouraged to hold their heads down in shame. That’s all well and good, but the problem with using CSS for layout is that it can be more difficult to work with CSS than HTML tables. For example, to achieve a standard three-column layout, you either need to use absolute positioning or floats. Here’s a three-column layout with floats: <style type="text/css"> #container { min-width: 800px; } #leftColumn { float: left; width: 300px; height: 100%; background-color:red; } #middleColumn { background-color:green; height: 100%; } #rightColumn { float: right; width: 300px; height: 100%; background-color:blue; } </style> <div id="container"> <div id="rightColumn"> Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column </div> <div id="leftColumn"> Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column </div> <div id="middleColumn"> Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column </div> </div> The page above contains four DIV elements: a container DIV which contains a leftColumn, middleColumn, and rightColumn DIV. The leftColumn DIV element is floated to the left and the rightColumn DIV element is floated to the right. Notice that the rightColumn DIV appears in the page before the middleColumn DIV – this unintuitive ordering is necessary to get the floats to work correctly (see http://stackoverflow.com/questions/533607/css-three-column-layout-problem). The page above (almost) works with the most recent versions of most browsers. For example, you get the correct three-column layout in both Firefox and Chrome: And the layout mostly works with Internet Explorer 9 except for the fact that for some strange reason the min-width doesn’t work so when you shrink the width of your browser, you can get the following unwanted layout: Notice how the middle column (the green column) bleeds to the left and right. People have solved these issues with more complicated CSS. For example, see: http://matthewjamestaylor.com/blog/holy-grail-no-quirks-mode.htm But, at this point, no one could argue that using CSS is easier or more intuitive than tables. It takes work to get a layout with CSS and we know that we could achieve the same layout more easily using HTML tables. Using CSS Grid Layout CSS Grid Layout is a new W3C standard which provides you with all of the benefits of using HTML tables for layout without the disadvantage of using an HTML TABLE element. In other words, CSS Grid Layout enables you to perform table layouts using pure Cascading Style Sheets. The CSS Grid Layout standard is still in a “Working Draft” state (it is not finalized) and it is located here: http://www.w3.org/TR/css3-grid-layout/ The CSS Grid Layout standard is only supported by Internet Explorer 10 and there are no signs that any browser other than Internet Explorer will support this standard in the near future. This means that it is only practical to take advantage of CSS Grid Layout when building Metro style applications with JavaScript. Here’s how you can create a standard three-column layout using a CSS Grid Layout: <!DOCTYPE html> <html> <head> <style type="text/css"> html, body, #container { height: 100%; padding: 0px; margin: 0px; } #container { display: -ms-grid; -ms-grid-columns: 300px auto 300px; -ms-grid-rows: 100%; } #leftColumn { -ms-grid-column: 1; background-color:red; } #middleColumn { -ms-grid-column: 2; background-color:green; } #rightColumn { -ms-grid-column: 3; background-color:blue; } </style> </head> <body> <div id="container"> <div id="leftColumn"> Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column </div> <div id="middleColumn"> Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column </div> <div id="rightColumn"> Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column </div> </div> </body> </html> When the page above is rendered in Internet Explorer 10, you get a standard three-column layout: The page above contains four DIV elements: a container DIV which contains a leftColumn DIV, middleColumn DIV, and rightColumn DIV. The container DIV is set to Grid display mode with the following CSS rule: #container { display: -ms-grid; -ms-grid-columns: 300px auto 300px; -ms-grid-rows: 100%; } The display property is set to the value “-ms-grid”. This property causes the container DIV to lay out its child elements in a grid. (Notice that you use “-ms-grid” instead of “grid”. The “-ms-“ prefix is used because the CSS Grid Layout standard is still preliminary. This implementation only works with IE10 and it might change before the final release.) The grid columns and rows are defined with the “-ms-grid-columns” and “-ms-grid-rows” properties. The style rule above creates a grid with three columns and one row. The left and right columns are fixed sized at 300 pixels. The middle column sizes automatically depending on the remaining space available. The leftColumn, middleColumn, and rightColumn DIVs are positioned within the container grid element with the following CSS rules: #leftColumn { -ms-grid-column: 1; background-color:red; } #middleColumn { -ms-grid-column: 2; background-color:green; } #rightColumn { -ms-grid-column: 3; background-color:blue; } The “-ms-grid-column” property is used to specify the column associated with the element selected by the style sheet selector. The leftColumn DIV is positioned in the first grid column, the middleColumn DIV is positioned in the second grid column, and the rightColumn DIV is positioned in the third grid column. I find using CSS Grid Layout to be just as intuitive as using an HTML table for layout. You define your columns and rows and then you position different elements within these columns and rows. Very straightforward. Creating Multiple Columns and Rows In the previous section, we created a super simple three-column layout. This layout contained only a single row. In this section, let’s create a slightly more complicated layout which contains more than one row: The following page contains a header row, a content row, and a footer row. The content row contains three columns: <!DOCTYPE html> <html> <head> <style type="text/css"> html, body, #container { height: 100%; padding: 0px; margin: 0px; } #container { display: -ms-grid; -ms-grid-columns: 300px auto 300px; -ms-grid-rows: 100px 1fr 100px; } #header { -ms-grid-column: 1; -ms-grid-column-span: 3; -ms-grid-row: 1; background-color: yellow; } #leftColumn { -ms-grid-column: 1; -ms-grid-row: 2; background-color:red; } #middleColumn { -ms-grid-column: 2; -ms-grid-row: 2; background-color:green; } #rightColumn { -ms-grid-column: 3; -ms-grid-row: 2; background-color:blue; } #footer { -ms-grid-column: 1; -ms-grid-column-span: 3; -ms-grid-row: 3; background-color: orange; } </style> </head> <body> <div id="container"> <div id="header"> Header, Header, Header </div> <div id="leftColumn"> Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column, Left Column </div> <div id="middleColumn"> Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column, Middle Column </div> <div id="rightColumn"> Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column, Right Column </div> <div id="footer"> Footer, Footer, Footer </div> </div> </body> </html> In the page above, the grid layout is created with the following rule which creates a grid with three rows and three columns: #container { display: -ms-grid; -ms-grid-columns: 300px auto 300px; -ms-grid-rows: 100px 1fr 100px; } The header is created with the following rule: #header { -ms-grid-column: 1; -ms-grid-column-span: 3; -ms-grid-row: 1; background-color: yellow; } The header is positioned in column 1 and row 1. Furthermore, notice that the “-ms-grid-column-span” property is used to span the header across three columns. CSS Grid Layout and Fractional Units When you use CSS Grid Layout, you can take advantage of fractional units. Fractional units provide you with an easy way of dividing up remaining space in a page. Imagine, for example, that you want to create a three-column page layout. You want the size of the first column to be fixed at 200 pixels and you want to divide the remaining space among the remaining three columns. The width of the second column is equal to the combined width of the third and fourth columns. The following CSS rule creates four columns with the desired widths: #container { display: -ms-grid; -ms-grid-columns: 200px 2fr 1fr 1fr; -ms-grid-rows: 1fr; } The fr unit represents a fraction. The grid above contains four columns. The second column is two times the size (2fr) of the third (1fr) and fourth (1fr) columns. When you use the fractional unit, the remaining space is divided up using fractional amounts. Notice that the single row is set to a height of 1fr. The single grid row gobbles up the entire vertical space. Here’s the entire HTML page: <!DOCTYPE html> <html> <head> <style type="text/css"> html, body, #container { height: 100%; padding: 0px; margin: 0px; } #container { display: -ms-grid; -ms-grid-columns: 200px 2fr 1fr 1fr; -ms-grid-rows: 1fr; } #firstColumn { -ms-grid-column: 1; background-color:red; } #secondColumn { -ms-grid-column: 2; background-color:green; } #thirdColumn { -ms-grid-column: 3; background-color:blue; } #fourthColumn { -ms-grid-column: 4; background-color:orange; } </style> </head> <body> <div id="container"> <div id="firstColumn"> First Column, First Column, First Column </div> <div id="secondColumn"> Second Column, Second Column, Second Column </div> <div id="thirdColumn"> Third Column, Third Column, Third Column </div> <div id="fourthColumn"> Fourth Column, Fourth Column, Fourth Column </div> </div> </body> </html>   Summary There is more in the CSS 3 Grid Layout standard than discussed in this blog post. My goal was to describe the basics. If you want to learn more than you can read through the entire standard at http://www.w3.org/TR/css3-grid-layout/ In this blog post, I described some of the difficulties that you might encounter when attempting to replace HTML tables with Cascading Style Sheets when laying out a web page. I explained how you can take advantage of the CSS 3 Grid Layout standard to avoid these problems when building Metro style applications using JavaScript. CSS 3 Grid Layout provides you with all of the benefits of using HTML tables for laying out a page without requiring you to use HTML table elements.

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  • Throttling in OSB

    - by Knut Vatsendvik
    Technorati Tags: soa,integration,osb,throttling,overload protection A common problem with integration is the risk of overloading a particular web service. When the capacity of a web service is reached and it continues to accept connections, it will most likely start to deteriorate. Fortunately there are 2 techniques, with Oracle Service Bus, that you can apply for protecting this from happening. You can either limit the concurrent number of requests for a Business Service (outbound requests) or you can limit the number of threads processing the requests for a Proxy Service (inbound requests). Limiting the Concurrent Number of Requests Limiting the concurrent requests for a Business Service cannot be set at design time so you have to use the built-in Oracle Service Bus Administration Console to do it (/sbconsole). Follow these steps to enable it: In Change Center, click Create to start a new Session Select Project Explorer, and navigate to the Business Service you want to limit Select the Operational Settings tab of the View a Business Service page In this tab, under Throttling, select the Enable check box. By enabling throttling you Specify a value for Maximum Concurrency Specify a positive integer value for Throttling Queue to backlog messages that has exceeded the message concurrency limit Specify the maximum time in milliseconds for Message Expiration a message can spend in Throttling Queue Click Update Click Active in Change Center to active the new settings If you re-publish the service, it will not overwrite the settings. Only if the resource is renamed or moved, it will. Please note that a throttling queue is an in-memory queue. Messages that are placed in this queue are not recoverable when a server fails or when you restart a server. Limiting the Number of Threads A better approach, in my opinion, is to limit the number of threads that can work with request. Follow these steps to do it: Open the WebLogic Server Console (/console) In Change Center, click Create to start a new Session In the left pane expand Environment and select Work Managers In the Global Work Managers page, click New    Click the Work Manager radio button, then click Next Enter a Name for the new Work Manager, and click Next In the Available Targets list, select server instances or clusters on which you will deploy applications that reference the Work Manager Click Finish. The new Work Manager now appears in the Global Work Managers page. Select the new Work Manager Right next to the Maximum Threads Constraint drop-down box, click New   Click the Maximum Threads Constraint radio button, then click Next Enter a Name and a thread Count to be the maximum size to allocate for requests. Click Next  In the Available Targets list, select server instances or clusters on which you will deploy applications that reference the Work Manager Click Finish Click Save Click Active in Change Center to active your changes.  A restart may be necessary.   Puh! Almost there. Start a new session. Go to the Service Bus Console (/sbconsole) and find your consuming Proxy Service. Click the Edit button of the Transport Configuration tab. Click Next Set the Dispatch Policy to the new Work Manager Click Last Click Save Click Active in Change Center to active your changes. 

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  • SPARC T4-2 Produces World Record Oracle Essbase Aggregate Storage Benchmark Result

    - by Brian
    Significance of Results Oracle's SPARC T4-2 server configured with a Sun Storage F5100 Flash Array and running Oracle Solaris 10 with Oracle Database 11g has achieved exceptional performance for the Oracle Essbase Aggregate Storage Option benchmark. The benchmark has upwards of 1 billion records, 15 dimensions and millions of members. Oracle Essbase is a multi-dimensional online analytical processing (OLAP) server and is well-suited to work well with SPARC T4 servers. The SPARC T4-2 server (2 cpus) running Oracle Essbase 11.1.2.2.100 outperformed the previous published results on Oracle's SPARC Enterprise M5000 server (4 cpus) with Oracle Essbase 11.1.1.3 on Oracle Solaris 10 by 80%, 32% and 2x performance improvement on Data Loading, Default Aggregation and Usage Based Aggregation, respectively. The SPARC T4-2 server with Sun Storage F5100 Flash Array and Oracle Essbase running on Oracle Solaris 10 achieves sub-second query response times for 20,000 users in a 15 dimension database. The SPARC T4-2 server configured with Oracle Essbase was able to aggregate and store values in the database for a 15 dimension cube in 398 minutes with 16 threads and in 484 minutes with 8 threads. The Sun Storage F5100 Flash Array provides more than a 20% improvement out-of-the-box compared to a mid-size fiber channel disk array for default aggregation and user-based aggregation. The Sun Storage F5100 Flash Array with Oracle Essbase provides the best combination for large Oracle Essbase databases leveraging Oracle Solaris ZFS and taking advantage of high bandwidth for faster load and aggregation. Oracle Fusion Middleware provides a family of complete, integrated, hot pluggable and best-of-breed products known for enabling enterprise customers to create and run agile and intelligent business applications. Oracle Essbase's performance demonstrates why so many customers rely on Oracle Fusion Middleware as their foundation for innovation. Performance Landscape System Data Size(millions of items) Database Load(minutes) Default Aggregation(minutes) Usage Based Aggregation(minutes) SPARC T4-2, 2 x SPARC T4 2.85 GHz 1000 149 398* 55 Sun M5000, 4 x SPARC64 VII 2.53 GHz 1000 269 526 115 Sun M5000, 4 x SPARC64 VII 2.4 GHz 400 120 448 18 * – 398 mins with CALCPARALLEL set to 16; 484 mins with CALCPARALLEL threads set to 8 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 2 x 2.85 GHz SPARC T4 processors 128 GB memory 2 x 300 GB 10000 RPM SAS internal disks Storage Configuration: 1 x Sun Storage F5100 Flash Array 40 x 24 GB flash modules SAS HBA with 2 SAS channels Data Storage Scheme Striped - RAID 0 Oracle Solaris ZFS Software Configuration: Oracle Solaris 10 8/11 Installer V 11.1.2.2.100 Oracle Essbase Client v 11.1.2.2.100 Oracle Essbase v 11.1.2.2.100 Oracle Essbase Administration services 64-bit Oracle Database 11g Release 2 (11.2.0.3) HP's Mercury Interactive QuickTest Professional 9.5.0 Benchmark Description The objective of the Oracle Essbase Aggregate Storage Option benchmark is to showcase the ability of Oracle Essbase to scale in terms of user population and data volume for large enterprise deployments. Typical administrative and end-user operations for OLAP applications were simulated to produce benchmark results. The benchmark test results include: Database Load: Time elapsed to build a database including outline and data load. Default Aggregation: Time elapsed to build aggregation. User Based Aggregation: Time elapsed of the aggregate views proposed as a result of tracked retrieval queries. Summary of the data used for this benchmark: 40 flat files, each of size 1.2 GB, 49.4 GB in total 10 million rows per file, 1 billion rows total 28 columns of data per row Database outline has 15 dimensions (five of them are attribute dimensions) Customer dimension has 13.3 million members 3 rule files Key Points and Best Practices The Sun Storage F5100 Flash Array has been used to accelerate the application performance. Setting data load threads (DLTHREADSPREPARE) to 64 and Load Buffer to 6 improved dataloading by about 9%. Factors influencing aggregation materialization performance are "Aggregate Storage Cache" and "Number of Threads" (CALCPARALLEL) for parallel view materialization. The optimal values for this workload on the SPARC T4-2 server were: Aggregate Storage Cache: 32 GB CALCPARALLEL: 16   See Also Oracle Essbase Aggregate Storage Option Benchmark on Oracle's SPARC T4-2 Server oracle.com Oracle Essbase oracle.com OTN SPARC T4-2 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 28 August 2012.

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  • Efficiently separating Read/Compute/Write steps for concurrent processing of entities in Entity/Component systems

    - by TravisG
    Setup I have an entity-component architecture where Entities can have a set of attributes (which are pure data with no behavior) and there exist systems that run the entity logic which act on that data. Essentially, in somewhat pseudo-code: Entity { id; map<id_type, Attribute> attributes; } System { update(); vector<Entity> entities; } A system that just moves along all entities at a constant rate might be MovementSystem extends System { update() { for each entity in entities position = entity.attributes["position"]; position += vec3(1,1,1); } } Essentially, I'm trying to parallelise update() as efficiently as possible. This can be done by running entire systems in parallel, or by giving each update() of one system a couple of components so different threads can execute the update of the same system, but for a different subset of entities registered with that system. Problem In reality, these systems sometimes require that entities interact(/read/write data from/to) each other, sometimes within the same system (e.g. an AI system that reads state from other entities surrounding the current processed entity), but sometimes between different systems that depend on each other (i.e. a movement system that requires data from a system that processes user input). Now, when trying to parallelize the update phases of entity/component systems, the phases in which data (components/attributes) from Entities are read and used to compute something, and the phase where the modified data is written back to entities need to be separated in order to avoid data races. Otherwise the only way (not taking into account just "critical section"ing everything) to avoid them is to serialize parts of the update process that depend on other parts. This seems ugly. To me it would seem more elegant to be able to (ideally) have all processing running in parallel, where a system may read data from all entities as it wishes, but doesn't write modifications to that data back until some later point. The fact that this is even possible is based on the assumption that modification write-backs are usually very small in complexity, and don't require much performance, whereas computations are very expensive (relatively). So the overhead added by a delayed-write phase might be evened out by more efficient updating of entities (by having threads work more % of the time instead of waiting). A concrete example of this might be a system that updates physics. The system needs to both read and write a lot of data to and from entities. Optimally, there would be a system in place where all available threads update a subset of all entities registered with the physics system. In the case of the physics system this isn't trivially possible because of race conditions. So without a workaround, we would have to find other systems to run in parallel (which don't modify the same data as the physics system), other wise the remaining threads are waiting and wasting time. However, that has disadvantages Practically, the L3 cache is pretty much always better utilized when updating a large system with multiple threads, as opposed to multiple systems at once, which all act on different sets of data. Finding and assembling other systems to run in parallel can be extremely time consuming to design well enough to optimize performance. Sometimes, it might even not be possible at all because a system just depends on data that is touched by all other systems. Solution? In my thinking, a possible solution would be a system where reading/updating and writing of data is separated, so that in one expensive phase, systems only read data and compute what they need to compute, and then in a separate, performance-wise cheap, write phase, attributes of entities that needed to be modified are finally written back to the entities. The Question How might such a system be implemented to achieve optimal performance, as well as making programmer life easier? What are the implementation details of such a system and what might have to be changed in the existing EC-architecture to accommodate this solution?

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  • 7 Steps To Cut Recruiting Costs & Drive Exceptional Business Results

    - by Oracle Accelerate for Midsize Companies
    By Steve Viarengo, Vice President Product Management, Oracle Taleo Cloud Services  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 In good times, trimming operational costs is an ongoing goal. In tough times, it’s a necessity. In both good times and bad, however, recruiting occurs. Growth increases headcount in good times, and opportunistic or replacement hiring occurs in slow business cycles. By employing creative recruiting strategies in tandem with the latest technology developments, you can reduce recruiting costs while driving exceptional business results. Here are some critical areas to focus on. 1.  Target Direct Cost Savings Total recruiting process expenses are the sum of external costs plus internal labor costs. Most organizations can reduce recruiting expenses with direct cost savings. While additional savings on indirect costs can be realized from process improvement and efficiency gains, there are direct cost savings and benefits readily available in three broad areas: sourcing, assessments, and green recruiting. 2. Sourcing: Reduce Agency Costs Agency search firm fees can amount to 35 percent of a new employee’s annual base salary. Typically taken from the hiring department budget, these fees may not be visible to HR. By relying on internal mobility programs, referrals, candidate pipelines, and corporate career Websites, organizations can reduce or eliminate this agency spend. And when you do have to pay third-party agency fees, you can optimize the value you receive by collaborating with agencies to identify referred candidates, ensure access to candidate data and history, and receive automatic notifications and correspondence. 3. Sourcing: Reduce Advertising Costs You can realize significant cost reductions by placing all job positions on your corporate career Website. This will allow you to reap a substantial number of candidates at minimal cost compared to job boards and other sourcing options. 4.  Sourcing: Internal Talent Pool Internal talent pools provide a way to reduce sourcing and advertising costs while delivering improved productivity and retention. Internal redeployment reduces costs and ramp-up time while increasing retention and employee satisfaction. 5.  Sourcing: External Talent Pool Strategic recruiting requires identifying and matching people with a given set of skills to a particular job while efficiently allocating sourcing expenditures. By using an e-recruiting system (which drives external talent pool management) with a candidate relationship database, you can automate prescreening and candidate matching while communicating with targeted candidates. Candidate relationship management can lower sourcing costs by marketing new job opportunities to candidates sourced in the past. By mining the talent pool in this fashion, you eliminate the need to source a new pool of candidates for each new requisition. Managing and mining the corporate candidate database can reduce the sourcing cost per candidate by as much as 50 percent. 6.  Assessments: Reduce Turnover Costs By taking advantage of assessments during the recruitment process, you can achieve a range of benefits, including better productivity, superior candidate performance, and lower turnover (providing considerable savings). Assessments also save recruiter and hiring manager time by focusing on a short list of qualified candidates. Hired for fit, such candidates tend to stay with the organization and produce quality work—ultimately driving revenue.  7. Green Recruiting: Reduce Paper and Processing Costs You can reduce recruiting costs by automating the process—and making it green. A paperless process informs candidates that you’re dedicated to green recruiting. It also leads to direct cost savings. E-recruiting reduces energy use and pollution associated with manufacturing, transporting, and recycling paper products. And process automation saves energy in mailing, storage, handling, filing, and reporting tasks. Direct cost savings come from reduced paperwork related to résumés, advertising, and onboarding. Improving the recruiting process through sourcing, assessments, and green recruiting not only saves costs. It also positions the company to improve the talent base during the recession while retaining the ability to grow appropriately in recovery. /* 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"; mso-bidi-font-family:"Times New Roman";} 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"; mso-bidi-font-family:"Times New Roman";}

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