Search Results

Search found 7538 results on 302 pages for 'parallel processing'.

Page 6/302 | < Previous Page | 2 3 4 5 6 7 8 9 10 11 12 13  | Next Page >

  • running a parallel port controlling program through php.

    - by prateek
    I have a program that is interacting with hardware via parallel port programming. i had compiled it and using its object file to interact with the hardware (a simple led). when i execute it directly on the shell it serves the purpose of glowing the LED but when i execute it using shell_exec() in php the command is executed but unable to interact with the hardware. i am totally confused.. .

    Read the article

  • Parallel programming in C#

    - by Alxandr
    I'm interested in learning about parallel programming in C#.NET (not like everything there is to know, but the basics and maybe some good-practices), therefore I've decided to reprogram an old program of mine which is called ImageSyncer. ImageSyncer is a really simple program, all it does is to scan trough a folder and find all files ending with .jpg, then it calculates the new position of the files based on the date they were taken (parsing of xif-data, or whatever it's called). After a location has been generated the program checks for any existing files at that location, and if one exist it looks at the last write-time of both the file to copy, and the file "in its way". If those are equal the file is skipped. If not a md5 checksum of both files is created and matched. If there is no match the file to be copied is given a new location to be copied to (for instance, if it was to be copied to "C:\test.jpg" it's copied to "C:\test(1).jpg" instead). The result of this operation is populated into a queue of a struct-type that contains two strings, the original file and the position to copy it to. Then that queue is iterated over untill it is empty and the files are copied. In other words there are 4 operations: 1. Scan directory for jpegs 2. Parse files for xif and generate copy-location 3. Check for file existence and if needed generate new path 4. Copy files And so I want to rewrite this program to make it paralell and be able to perform several of the operations at the same time, and I was wondering what the best way to achieve that would be. I've came up with two different models I can think of, but neither one of them might be any good at all. The first one is to parallelize the 4 steps of the old program, so that when step one is to be executed it's done on several threads, and when the entire of step 1 is finished step 2 is began. The other one (which I find more interesting because I have no idea of how to do that) is to create a sort of worker and consumer model, so when a thread is finished with step 1 another one takes over and performs step 2 at that object (or something like that). But as said, I don't know if any of these are any good solutions. Also, I don't know much about parallel programming at all. I know how to make a thread, and how to make it perform a function taking in an object as its only parameter, and I've also used the BackgroundWorker-class on one occasion, but I'm not that familiar with any of them. Any input would be appreciated.

    Read the article

  • Gamepad Control for Processing + Android to Control Arduino Robot

    - by Iker
    I would like to create a Multitouch Gamepad control for Processing and use it to control a remote Arduino Robot. I would like to make the GUI on Processing and compile it for Android. Here is the GUI Gamepad for Processing I have created so far: float easing = 0.09; // start position int posX = 50; int posY = 200; // target position int targetX = 50; int targetY = 200; boolean dragging = false; void setup() { size(500,250); smooth(); } void draw() { background(255); if (!dragging) { // calculate the difference in position, apply easing and add to vx/vy float vx = (targetX - (posX)) * easing; float vy = (targetY - (posY)) * easing; // Add the velocity to the current position: make it move! posX += vx; posY += vy; } if(mousePressed) { dragging = true; posX = mouseX; posY = mouseY; } else { dragging = false; } DrawGamepad(); DrawButtons(); } void DrawGamepad() { //fill(0,155,155); //rect(0, 150, 100, 100, 15); ellipseMode(RADIUS); // Set ellipseMode to RADIUS fill(0,155,155); // Set fill to blue ellipse(50, 200, 50, 50); // Draw white ellipse using RADIUS mode ellipseMode(CENTER); // Set ellipseMode to CENTER fill(255); // Set fill to white// ellipse(posX, posY, 35, 35); // Draw gray ellipse using CENTER mode } void DrawButtons() { fill(0,155,155); // Set fill to blue ellipse(425, 225, 35, 35); ellipse(475, 225, 35, 35); fill(255,0,0); // Set fill to blue ellipse(425, 175, 35, 35); ellipse(475, 175, 35, 35); } I have realized that probably that code will not support Multitouch events on Android so I came up with another code found on this link Can Processing handle multi-touch? So the aim of this project is to create de multitouch gamepad to use to control my Arduino Robot. The gamepad should detect which key was pressed as well as the direction of the Joystick. Any help appreciated.

    Read the article

  • JRuby-friendly method for parallel-testing Rails app

    - by Toby Hede
    I am looking for a system to parallelise a large suite of tests in a Ruby on Rails app (using rspec, cucumber) that works using JRuby. Cucumber is actually not too bad, but the full rSpec suite currently takes nearly 20 minutes to run. The systems I can find (hydra, parallel-test) look like they use forking, which isn't the ideal solution for the JRuby environment.

    Read the article

  • Unified Parallel C - examples and list of extensions

    - by osgx
    Hello Where can I find examples of code, written in "Unified Parallel C"? I also interested in normative documents about this language (standards, reference manuals, online-accessible books and courses). What extensions were added to C to get UPC? Is this dialect alive or dead?

    Read the article

  • Annotation Processing Virtual Mini-Track at JavaOne 2012

    - by darcy
    Putting together the list of JavaOne talks I'm interested in attending, I noticed there is a virtual mini-track on annotation processing and related technology this year, with a combination of bofs, sessions, and a hands-on-lab: Monday Multidevice Content Display and a Smart Use of Annotation Processing, Dimitri BAELI and Gilles Di Guglielmo Tuesday Advanced Annotation Processing with JSR 269, Jaroslav Tulach Build Your Own Type System for Fun and Profit, Werner Dietl and Michael Ernst Wednesday Annotations and Annotation Processing: What’s New in JDK 8?, Joel Borggrén-Franck Thursday Hack into Your Compiler!, Jaroslav Tulach Writing Annotation Processors to Aid Your Development Process, Ian Robertson As the lead engineer on bot apt (rest in peace) in JDK 5 and JSR 269 in JDK 6, I'd be heartened to see greater adoption and use of annotation processing by Java developers.

    Read the article

  • Send raw data to USB parallel port after upgrading to 11.10

    - by zaphod
    I have a laser cutter connected via a generic USB to parallel adapter. The laser cutter speaks HPGL, as it happens, but since this is a laser cutter and not a plotter, I usually want to generate the HPGL myself, since I care about the ordering, speed, and direction of cuts and so on. In previous versions of Ubuntu, I was able to print to the cutter by copying an HPGL file directly to the corresponding USB "lp" device. For example: cp foo.plt /dev/usblp1 Well, I just upgraded to Ubuntu 11.10 oneiric, and I can't find any "lp" devices in /dev anymore. D'oh! What's the preferred way to send raw data to a parallel port in Ubuntu? I've tried System Settings Printing + Add, hoping that I might be able to associate my device with some kind of "raw printer" driver and print to it with a command like lp -d LaserCutter foo.plt But my USB to parallel adapter doesn't seem to show up in the list. What I do see are my HP Color LaserJet, two USB-to-serial adapters, "Enter URI", and "Network Printer". Meanwhile, over in /dev, I do see /dev/ttyUSB0 and /dev/ttyUSB1 devices for the 2 USB-to-serial adapters. I don't see anything obvious corresponding to the HP printer (which was /dev/usblp0 prior to the upgrade), except for generic USB stuff. For example, sudo find /dev | grep lp produces no output. I do seem to be able to print to the HP printer just fine, though. The printer setup GUI gives it a device URI starting with "hp:" which isn't much help for the parallel adapter. The CUPS administrator's guide makes it sound like I might need to feed it a device URI of the form parallel:/dev/SOMETHING, but of course if I had a /dev/SOMETHING I'd probably just go on writing to it directly. Here's what dmesg says after I disconnect and reconnect the device from the USB port: [ 924.722906] usb 1-1.1.4: USB disconnect, device number 7 [ 959.993002] usb 1-1.1.4: new full speed USB device number 8 using ehci_hcd And here's how it shows up in lsusb -v: Bus 001 Device 008: ID 1a86:7584 QinHeng Electronics CH340S Device Descriptor: bLength 18 bDescriptorType 1 bcdUSB 1.10 bDeviceClass 0 (Defined at Interface level) bDeviceSubClass 0 bDeviceProtocol 0 bMaxPacketSize0 8 idVendor 0x1a86 QinHeng Electronics idProduct 0x7584 CH340S bcdDevice 2.52 iManufacturer 0 iProduct 2 USB2.0-Print iSerial 0 bNumConfigurations 1 Configuration Descriptor: bLength 9 bDescriptorType 2 wTotalLength 32 bNumInterfaces 1 bConfigurationValue 1 iConfiguration 0 bmAttributes 0x80 (Bus Powered) MaxPower 96mA Interface Descriptor: bLength 9 bDescriptorType 4 bInterfaceNumber 0 bAlternateSetting 0 bNumEndpoints 2 bInterfaceClass 7 Printer bInterfaceSubClass 1 Printer bInterfaceProtocol 2 Bidirectional iInterface 0 Endpoint Descriptor: bLength 7 bDescriptorType 5 bEndpointAddress 0x82 EP 2 IN bmAttributes 2 Transfer Type Bulk Synch Type None Usage Type Data wMaxPacketSize 0x0020 1x 32 bytes bInterval 0 Endpoint Descriptor: bLength 7 bDescriptorType 5 bEndpointAddress 0x02 EP 2 OUT bmAttributes 2 Transfer Type Bulk Synch Type None Usage Type Data wMaxPacketSize 0x0020 1x 32 bytes bInterval 0 Device Status: 0x0000 (Bus Powered)

    Read the article

  • Send raw data to USB parallel port after upgrading to 11.10 oneiric

    - by zaphod
    I have a laser cutter connected via a generic USB to parallel adapter. The laser cutter speaks HPGL, as it happens, but since this is a laser cutter and not a plotter, I usually want to generate the HPGL myself, since I care about the ordering, speed, and direction of cuts and so on. In previous versions of Ubuntu, I was able to print to the cutter by copying an HPGL file directly to the corresponding USB "lp" device. For example: cp foo.plt /dev/usblp1 Well, I just upgraded to Ubuntu 11.10 oneiric, and I can't find any "lp" devices in /dev anymore. D'oh! What's the preferred way to send raw data to a parallel port in Ubuntu? I've tried System Settings Printing + Add, hoping that I might be able to associate my device with some kind of "raw printer" driver and print to it with a command like lp -d LaserCutter foo.plt But my USB to parallel adapter doesn't seem to show up in the list. What I do see are my HP Color LaserJet, two USB-to-serial adapters, "Enter URI", and "Network Printer". Meanwhile, over in /dev, I do see /dev/ttyUSB0 and /dev/ttyUSB1 devices for the 2 USB-to-serial adapters. I don't see anything obvious corresponding to the HP printer (which was /dev/usblp0 prior to the upgrade), except for generic USB stuff. For example, sudo find /dev | grep lp produces no output. I do seem to be able to print to the HP printer just fine, though. The printer setup GUI gives it a device URI starting with "hp:" which isn't much help for the parallel adapter. The CUPS administrator's guide makes it sound like I might need to feed it a device URI of the form parallel:/dev/SOMETHING, but of course if I had a /dev/SOMETHING I'd probably just go on writing to it directly. Here's what dmesg says after I disconnect and reconnect the device from the USB port: [ 924.722906] usb 1-1.1.4: USB disconnect, device number 7 [ 959.993002] usb 1-1.1.4: new full speed USB device number 8 using ehci_hcd And here's how it shows up in lsusb -v: Bus 001 Device 008: ID 1a86:7584 QinHeng Electronics CH340S Device Descriptor: bLength 18 bDescriptorType 1 bcdUSB 1.10 bDeviceClass 0 (Defined at Interface level) bDeviceSubClass 0 bDeviceProtocol 0 bMaxPacketSize0 8 idVendor 0x1a86 QinHeng Electronics idProduct 0x7584 CH340S bcdDevice 2.52 iManufacturer 0 iProduct 2 USB2.0-Print iSerial 0 bNumConfigurations 1 Configuration Descriptor: bLength 9 bDescriptorType 2 wTotalLength 32 bNumInterfaces 1 bConfigurationValue 1 iConfiguration 0 bmAttributes 0x80 (Bus Powered) MaxPower 96mA Interface Descriptor: bLength 9 bDescriptorType 4 bInterfaceNumber 0 bAlternateSetting 0 bNumEndpoints 2 bInterfaceClass 7 Printer bInterfaceSubClass 1 Printer bInterfaceProtocol 2 Bidirectional iInterface 0 Endpoint Descriptor: bLength 7 bDescriptorType 5 bEndpointAddress 0x82 EP 2 IN bmAttributes 2 Transfer Type Bulk Synch Type None Usage Type Data wMaxPacketSize 0x0020 1x 32 bytes bInterval 0 Endpoint Descriptor: bLength 7 bDescriptorType 5 bEndpointAddress 0x02 EP 2 OUT bmAttributes 2 Transfer Type Bulk Synch Type None Usage Type Data wMaxPacketSize 0x0020 1x 32 bytes bInterval 0 Device Status: 0x0000 (Bus Powered)

    Read the article

  • Recommendations for Open Source Parallel programming IDE

    - by Andrew Bolster
    What are the best IDE's / IDE plugins / Tools, etc for programming with CUDA / MPI etc? I've been working in these frameworks for a short while but feel like the IDE could be doing more heavy lifting in terms of scaling and job processing interactions. (I usually use Eclipse or Netbeans, and usually in C/C++ with occasional Java, and its a vague question but I can't think of any more specific way to put it)

    Read the article

  • Using TPL and PLINQ to raise performance of feed aggregator

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

    Read the article

  • Explaining Explain Plan Notes for Auto DOP

    - by jean-pierre.dijcks
    I've recently gotten some questions around "why do I not see a parallel plan" while Auto DOP is on (I think)...? It is probably worthwhile to quickly go over some of the ways to find out what Auto DOP was thinking. In general, there is no need to go tracing sessions and look under the hood. The thing to start with is to do an explain plan on your statement and to look at the parameter settings on the system. Parameter Settings to Look At First and foremost, make sure that parallel_degree_policy = AUTO. If you have that parameter set to LIMITED you will not have queuing and we will only do the auto magic if your objects are set to default parallel (so no degree specified). Next you want to look at the value of parallel_degree_limit. It is typically set to CPU, which in default settings equates to the Default DOP of the system. If you are testing Auto DOP itself and the impact it has on performance you may want to leave it at this CPU setting. If you are running concurrent statements you may want to give this some more thoughts. See here for more information. In general, do stick with either CPU or with a specific number. For now avoid the IO setting as I've seen some mixed results with that... In 11.2.0.2 you should also check that IO Calibrate has been run. Best to simply do a: SQL> select * from V$IO_CALIBRATION_STATUS; STATUS        CALIBRATION_TIME ------------- ---------------------------------------------------------------- READY         04-JAN-11 10.04.13.104 AM You should see that your IO Calibrate is READY and therefore Auto DOP is ready. In any case, if you did not run the IO Calibrate step you will get the following note in the explain plan: Note -----    - automatic DOP: skipped because of IO calibrate statistics are missing One more note on calibrate_io, if you do not have asynchronous IO enabled you will see:  ERROR at line 1: ORA-56708: Could not find any datafiles with asynchronous i/o capability ORA-06512: at "SYS.DBMS_RMIN", line 463 ORA-06512: at "SYS.DBMS_RESOURCE_MANAGER", line 1296 ORA-06512: at line 7 While this is changed in some fixes to the calibrate procedure, you should really consider switching asynchronous IO on for your data warehouse. Explain Plan Explanation To see the notes that are shown and explained here (and the above little snippet ) you can use a simple explain plan mechanism. There should  be no need to add +parallel etc. explain plan for <statement> SELECT PLAN_TABLE_OUTPUT FROM TABLE(DBMS_XPLAN.DISPLAY()); Auto DOP The note structure displaying why Auto DOP did not work (with the exception noted above on IO Calibrate) is like this: Automatic degree of parallelism is disabled: <reason> These are the reason codes: Parameter -  parallel_degree_policy = manual which will not allow Auto DOP to kick in  Hint - One of the following hints are used NOPARALLEL, PARALLEL(1), PARALLEL(MANUAL) Outline - A SQL outline of an older version (before 11.2) is used SQL property restriction - The statement type does not allow for parallel processing Rule-based mode - Instead of the Cost Based Optimizer the system is using the RBO Recursive SQL statement - The statement type does not allow for parallel processing pq disabled/pdml disabled/pddl disabled - For some reason (alter session?) parallelism is disabled Limited mode but no parallel objects referenced - your parallel_degree_policy = LIMITED and no objects in the statement are decorated with the default PARALLEL degree. In most cases all objects have a specific degree in which case Auto DOP will honor that degree. Parallel Degree Limited When Auto DOP does it works you may see the cap you imposed with parallel_degree_limit showing up in the note section of the explain plan: Note -----    - automatic DOP: Computed Degree of Parallelism is 16 because of degree limit This is an obvious indication that your are being capped for this statement. There is one quite interesting one that happens when you are being capped at DOP = 1. First of you get a serial plan and the note changes slightly in that it does not indicate it is being capped (we hope to update the note at some point in time to be more specific). It right now looks like this: Note -----    - automatic DOP: Computed Degree of Parallelism is 1 Dynamic Sampling With 11.2.0.2 you will start seeing another interesting change in parallel plans, and since we are talking about the note section here, I figured we throw this in for good measure. If we deem the parallel (!) statement complex enough, we will enact dynamic sampling on your query. This happens as long as you did not change the default for dynamic sampling on the system. The note looks like this: Note ----- - dynamic sampling used for this statement (level=5)

    Read the article

  • How to write C++ audio processing applications?

    - by cesko82
    Hi everyone, I'm an Electronics and Telecommunications student, next to my graduation. I'm gonna work on a project that involves my knowledge about DSP, music and audio in general. I allready know all the basic mathematic instruments and all the stuff I need to manage it, such as FFT, circular convolution ecc ecc. I want to learn C++ programming basically for one reason: it's very important in the professional world!!! And I think it's one of the most used to write applications working with audio, especially when it's about real time processing. Ok, after this small introduction I would like to know first, which are the most used libraries to work with audio processing in c++?? I was longer looking on the web but i couldn't find a lo of working stuff. (I work under linux with eclipse CDT enviroment). Then I would like to know if there are good sources to learn how to write some working code, such as for example how to write a simple low pass filter. Basically now i will not write real time applications, I would like to start from the processing of a WAV file, or even better an MP3 file, so basically on vectors of samples. Let's say that basically for now I would like to extract the waveform from an audio file, and save it to a thumbnail or to a PNG image. Ok, for now I think it's all I would need. Any ideas, advices, libraries, books, interesting sources about that? Thanks a lot in advance for any kind of answer. Giovanni.

    Read the article

  • Image processing on bifurcation diagram to get small eps size

    - by yCalleecharan
    Hello, I'm producing bifurcation diagrams (which are normally used in nonlinear dynamics). These diagrams identify abrupt changes in topologies due to stability changes. These abrupt changes occur as one or more parameters pass through some critical value(s). An example is here: http://en.wikipedia.org/wiki/File:LogisticMap_BifurcationDiagram.png On the above figure, some image processing has been done so as to make the plot more visually pleasant. A bifurcation diagram usually contains hundreds of thousands of points and the resulting eps file can become very big. Journal submission in the LaTeX format require that figures are to be submitted in the eps format. In my case one of such figures can result in about 6 MB in Matlab and even much more in Gnuplot. For the example in the above figure, 100,000 x values are calculated for each r and one can imagine that the resulting eps file would be huge. The site however explains some image processing that makes the plot more visually pleasing. Can anyone explain to me stepwise how go about? I can't understand the explanation provided in the "summary" section. Will the resulting image processing also reduce the figure size? Furthermore, any tips on reducing the file size of such a huge eps figure? Thanks a lot...

    Read the article

  • Software to create a virtual parallel port in Windows XP?

    - by drknexus
    I am writing a program that will eventually be used on a computer with a physical parallel port and will need to set certain pins high or low in order to signal to an external device. However, the development laptop I am using does not have any physical parallel ports and is too low powered to run a virtual machine. Is there any option available that will create a virtual parallel port within Windows XP? Ideally it would include a debug mode that would allow me to see what values have been pushed out on the parallel port.

    Read the article

  • Parallel Computing Platform Developer Lab

    - by Daniel Moth
    This is an exciting announcement that I must share: "Microsoft Developer & Platform Evangelism, in collaboration with the Microsoft Parallel Computing Platform product team, is hosting a developer lab at the Platform Adoption Center on April 12-15, 2010.  This event is for Microsoft Partners and Customers seeking to incorporate either .NET Framework 4 or Visual C++ 2010 parallelism features into their new or existing applications, and to gain expertise with new Visual Studio 2010 tools including the Parallel Tasks and Parallel Stacks debugger toolwindows, and the Concurrency Visualizer in the profiler. Opportunities for attendees include: Gain expert design assistance with your Parallel Computing Platform based solution. Develop a solution prototype in collaboration with Microsoft Software Engineers. Attend topical presentations and “chalk-talk” sessions. Your team will be assigned private, secure offices for confidential collaboration activities. The event has limited capacity, thus enrollment is based on an application process.   Please download and complete the application form then return it to the event management team per instructions included within the form.  Applications will be evaluated based upon the technical solution scenario along with indicated project readiness timelines.  Microsoft event management team members may contact you directly for additional clarification and discussion of your project scenario during the nomination process." Comments about this post welcome at the original blog.

    Read the article

  • An Overview of Batch Processing in Java EE 7

    - by Janice J. Heiss
    Up on otn/java is a new article by Oracle senior software engineer Mahesh Kannan, titled “An Overview of Batch Processing in Java EE 7.0,” which explains the new batch processing capabilities provided by JSR 352 in Java EE 7. Kannan explains that “Batch processing is used in many industries for tasks ranging from payroll processing; statement generation; end-of-day jobs such as interest calculation and ETL (extract, load, and transform) in a data warehouse; and many more. Typically, batch processing is bulk-oriented, non-interactive, and long running—and might be data- or computation-intensive. Batch jobs can be run on schedule or initiated on demand. Also, since batch jobs are typically long-running jobs, check-pointing and restarting are common features found in batch jobs.” JSR 352 defines the programming model for batch applications plus a runtime to run and manage batch jobs. The article covers feature highlights, selected APIs, the structure of Job Scheduling Language, and explains some of the key functions of JSR 352 using a simple payroll processing application. The article also describes how developers can run batch applications using GlassFish Server Open Source Edition 4.0. Kannan summarizes the article as follows: “In this article, we saw how to write, package, and run simple batch applications that use chunk-style steps. We also saw how the checkpoint feature of the batch runtime allows for the easy restart of failed batch jobs. Yet, we have barely scratched the surface of JSR 352. With the full set of Java EE components and features at your disposal, including servlets, EJB beans, CDI beans, EJB automatic timers, and so on, feature-rich batch applications can be written fairly easily.” Check out the article here.

    Read the article

  • Unity: parallel vectors and cross product, how to compare vectors

    - by Heisenbug
    I read this post explaining a method to understand if the angle between 2 given vectors and the normal to the plane described by them, is clockwise or anticlockwise: public static AngleDir GetAngleDirection(Vector3 beginDir, Vector3 endDir, Vector3 upDir) { Vector3 cross = Vector3.Cross(beginDir, endDir); float dot = Vector3.Dot(cross, upDir); if (dot > 0.0f) return AngleDir.CLOCK; else if (dot < 0.0f) return AngleDir.ANTICLOCK; return AngleDir.PARALLEL; } After having used it a little bit, I think it's wrong. If I supply the same vector as input (beginDir equal to endDir), the cross product is zero, but the dot product is a little bit more than zero. I think that to fix that I can simply check if the cross product is zero, means that the 2 vectors are parallel, but my code doesn't work. I tried the following solution: Vector3 cross = Vector3.Cross(beginDir, endDir); if (cross == Vector.zero) return AngleDir.PARALLEL; And it doesn't work because comparison between Vector.zero and cross is always different from zero (even if cross is actually [0.0f, 0.0f, 0.0f]). I tried also this: Vector3 cross = Vector3.Cross(beginDir, endDir); if (cross.magnitude == 0.0f) return AngleDir.PARALLEL; it also fails because magnitude is slightly more than zero. So my question is: given 2 Vector3 in Unity, how to compare them? I need the elegant equivalent version of this: if (beginDir.x == endDir.x && beginDir.y == endDir.y && beginDir.z == endDir.z) return true;

    Read the article

  • processing an audio wav file with C

    - by sa125
    Hi - I'm working on processing the amplitude of a wav file and scaling it by some decimal factor. I'm trying to wrap my head around how to read and re-write the file in a memory-efficient way while also trying to tackle the nuances of the language (I'm new to C). The file can be in either an 8- or 16-bit format. The way I thought of doing this is by first reading the header data into some pre-defined struct, and then processing the actual data in a loop where I'll read a chunk of data into a buffer, do whatever is needed to it, and then write it to the output. #include <stdio.h> #include <stdlib.h> typedef struct header { char chunk_id[4]; int chunk_size; char format[4]; char subchunk1_id[4]; int subchunk1_size; short int audio_format; short int num_channels; int sample_rate; int byte_rate; short int block_align; short int bits_per_sample; short int extra_param_size; char subchunk2_id[4]; int subchunk2_size; } header; typedef struct header* header_p; void scale_wav_file(char * input, float factor, int is_8bit) { FILE * infile = fopen(input, "rb"); FILE * outfile = fopen("outfile.wav", "wb"); int BUFSIZE = 4000, i, MAX_8BIT_AMP = 255, MAX_16BIT_AMP = 32678; // used for processing 8-bit file unsigned char inbuff8[BUFSIZE], outbuff8[BUFSIZE]; // used for processing 16-bit file short int inbuff16[BUFSIZE], outbuff16[BUFSIZE]; // header_p points to a header struct that contains the file's metadata fields header_p meta = (header_p)malloc(sizeof(header)); if (infile) { // read and write header data fread(meta, 1, sizeof(header), infile); fwrite(meta, 1, sizeof(meta), outfile); while (!feof(infile)) { if (is_8bit) { fread(inbuff8, 1, BUFSIZE, infile); } else { fread(inbuff16, 1, BUFSIZE, infile); } // scale amplitude for 8/16 bits for (i=0; i < BUFSIZE; ++i) { if (is_8bit) { outbuff8[i] = factor * inbuff8[i]; if ((int)outbuff8[i] > MAX_8BIT_AMP) { outbuff8[i] = MAX_8BIT_AMP; } } else { outbuff16[i] = factor * inbuff16[i]; if ((int)outbuff16[i] > MAX_16BIT_AMP) { outbuff16[i] = MAX_16BIT_AMP; } else if ((int)outbuff16[i] < -MAX_16BIT_AMP) { outbuff16[i] = -MAX_16BIT_AMP; } } } // write to output file for 8/16 bit if (is_8bit) { fwrite(outbuff8, 1, BUFSIZE, outfile); } else { fwrite(outbuff16, 1, BUFSIZE, outfile); } } } // cleanup if (infile) { fclose(infile); } if (outfile) { fclose(outfile); } if (meta) { free(meta); } } int main (int argc, char const *argv[]) { char infile[] = "file.wav"; float factor = 0.5; scale_wav_file(infile, factor, 0); return 0; } I'm getting differing file sizes at the end (by 1k or so, for a 40Mb file), and I suspect this is due to the fact that I'm writing an entire buffer to the output, even though the file may have terminated before filling the entire buffer size. Also, the output file is messed up - won't play or open - so I'm probably doing the whole thing wrong. Any tips on where I'm messing up will be great. Thanks!

    Read the article

  • Parallel EntityFramework

    - by mehanik
    Is it possible to make some work in parallel with entity framework for following example? using (var dbContext = new DB()) { var res = (from c in dbContext.Customers orderby c.Name select new { c.Id, c.Name, c.Role } ).ToDictionary(c => c.Id, c => new Dictionary<string, object> { { "Name",c.Name }, { "Role", c.Role } }); } For exampe what will be changed if I add AsParrallel? using (var dbContext = new DB()) { var res = (from c in dbContext.Customers orderby c.Name select new { c.Id, c.Name, c.Role } ).AsParallel().ToDictionary(c => c.Id, c => new Dictionary<string, object> { { "Name",c.Name }, { "Role", c.Role } }); }

    Read the article

  • What parallel programming model do you recommend today to take advantage of the manycore processors

    - by Doctor J
    If you were writing a new application from scratch today, and wanted it to scale to all the cores you could throw at it tomorrow, what parallel programming model/system/language/library would you choose? Why? I am particularly interested in answers along these axes: Programmer productivity / ease of use (can mortals successfully use it?) Target application domain (what problems is it (not) good at?) Concurrency style (does it support tasks, pipelines, data parallelism, messages...?) Maintainability / future-proofing (will anybody still be using it in 20 years?) Performance (how does it scale on what kinds of hardware?) I am being deliberately vauge on the nature of the application in anticipation of getting good general answers useful for a variety of applications.

    Read the article

  • Can Parallel.ForEach be used safely with CloudTableQuery

    - by knightpfhor
    I have a reasonable number of records in an Azure Table that I'm attempting to do some one time data encryption on. I thought that I could speed things up by using a Parallel.ForEach. Also because there are more than 1K records and I don't want to mess around with continuation tokens myself I'm using a CloudTableQuery to get my enumerator. My problem is that some of my records have been double encrypted and I realised that I'm not sure how thread safe the enumerator returned by CloudTableQuery.Execute() is. Has anyone else out there had any experience with this combination?

    Read the article

< Previous Page | 2 3 4 5 6 7 8 9 10 11 12 13  | Next Page >