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  • jQuery JSON help

    - by kim
    okay I'm new to jQuery and JSON but I have now done so I got some information from the database in JSON format and now I want to show the results in a nice way but I don't know how ;) what I want is to show 5 newest threads on my page so will this script try to load all the time or do I need to do something else? I want it to show the 5 newest threads and when there somes a new thread i should slide down and the 6 threads at the bottom should disappear Here is my code <script type="text/javascript"> $.getJSON('ajax/forumThreads', function(data) { //$('<p>' + data[0].overskrift + '</p>').appendTo('#updateMe > .overskrift'); $('<div class="overskrift">' + data[0].overskrift + '</div>') { $(this).hide().appendTo('updateMe').slideDown(1000); } //alert(data[0].overskrift); }); </script>

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  • Do I need to syncronize thread access to an int

    - by Martin Harris
    I've just written a method that is called by multiple threads simultaneously and I need to keep track of when all the threads have completed, the code uses this pattern: private void RunReport() { _reportsRunning++; try { //code to run the report } finally { _reportsRunning--; } } This is the only place within the code that _reportsRunning's value is changed, and the method takes about a second to run. Occasionally when I have more than six or so threads running reports together the final result for _reportsRunning can get down to -1, if I wrap the calls to _runningReports++ and _runningReports-- in a lock then the behaviour appears to be correct and consistant. So, to the question: When I was learning multithreading in C++ I was taught that you didn't need to synchronize calls to increment and decrement operations because they were always one assembly instruction and therefore it was impossible for the thread to be switched out mid-call. Was I taught correctly, and if so how come that doesn't hold true for C#?

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  • Simple C++ container class that is thread-safe for writing

    - by conradlee
    I am writing a multi-threaded program using OpenMP in C++. At one point my program forks into many threads, each of which need to add "jobs" to some container that keeps track of all added jobs. Each job can just be a pointer to some object. Basically, I just need the add pointers to some container from several threads at the same time. Is there a simple solution that performs well? After some googling, I found that STL containers are not thread-safe. Some stackoverflow threads address this question, but none that forms a consensus on a simple solution.

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  • Does thread pool size keep growing for scheduledthreadpoolexecutor?

    - by Sourajit Basak
    Imagine a situation where tasks are being added to scheduledthreadpoolexecutor. Each of these tasks will keep on running at different periodic intervals. Although all such tasks will not be running at the same time because each is set at different intervals, there may be a situation where a high number of threads are competing for execution. Is there any restriction on total number of threads ? It seems there is a restriction on the total number of idle threads. And does this concept of idle thread imply that long running tasks (thread) may be destroyed and recreated when needed ?

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  • Threaded application sleeps with other application

    - by DeeD
    I have a weird problem with my threaded software. I start 2 instances of the software. Each instance has 2 threads, one thread creates a socket to use, and the other one is uses the socket for communication. When one of the threads in one instance calls sleep(3), the other threads in the the other instance sleeps too. And the weirdest thing is that when I rebooted the computer, it works the first time, but after trying a second time, it sleeps like described. How is this possible? Is it using some shared resource?

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  • Debug.writeline locks

    - by Carra
    My program frequently stops with a deadlock. When I do a break-all and look at the threads I see that three threads are stuck in our logging function: public class Logging { public static void WriteClientLog(LogLevel logLevel, string message) { #if DEBUG System.Diagnostics.Debug.WriteLine(String.Format("{0} {1}", DateTime.Now.ToString("HH:mm:ss"), message)); //LOCK #endif //...Log4net logging } } If I let the program continue the threads are still stuck on that line. I can't see where this can lock. The debug class, string class & datetime class seem to be thread safe. The error goes away when I remove the "#if DEBUG System... #endif" code but I'm curious why this behavior happens. Thread one: public void CleanCache() { Logging.WriteClientLog(LogLevel.Debug, "Start clean cache.");//Stuck } Thread two: private void AliveThread() { Logging.WriteClientLog(LogLevel.Debug, "Check connection");//Stuck }

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  • [C++] Needed: A simple C++ container (stack, linked list) that is thread-safe for writing

    - by conradlee
    I am writing a multi-threaded program using OpenMP in C++. At one point my program forks into many threads, each of which need to add "jobs" to some container that keeps track of all added jobs. Each job can just be a pointer to some object. Basically, I just need the add pointers to some container from several threads at the same time. Is there a simple solution that performs well? After some googling, I found that STL containers are not thread-safe. Some stackoverflow threads address this question, but none form a consensus on a simple solution.

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  • Multi-threading does not work correctly using std::thread (C++ 11)

    - by user1364743
    I coded a small c++ program to try to understand how multi-threading works using std::thread. Here's the step of my program execution : Initialization of a 5x5 matrix of integers with a unique value '42' contained in the class 'Toto' (initialized in the main). I print the initialized 5x5 matrix. Declaration of std::vector of 5 threads. I attach all threads respectively with their task (threadTask method). Each thread will manipulate a std::vector<int> instance. I join all threads. I print the new state of my 5x5 matrix. Here's the output : 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 It should be : 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 42 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 4 4 4 4 4 Here's the code sample : #include <iostream> #include <vector> #include <thread> class Toto { public: /* ** Initialize a 5x5 matrix with the 42 value. */ void initData(void) { for (int y = 0; y < 5; y++) { std::vector<int> vec; for (int x = 0; x < 5; x++) { vec.push_back(42); } this->m_data.push_back(vec); } } /* ** Display the whole matrix. */ void printData(void) const { for (int y = 0; y < 5; y++) { for (int x = 0; x < 5; x++) { printf("%d ", this->m_data[y][x]); } printf("\n"); } printf("\n"); } /* ** Function attached to the thread (thread task). ** Replace the original '42' value by another one. */ void threadTask(std::vector<int> &list, int value) { for (int x = 0; x < 5; x++) { list[x] = value; } } /* ** Return the m_data instance propertie. */ std::vector<std::vector<int> > &getData(void) { return (this->m_data); } private: std::vector<std::vector<int> > m_data; }; int main(void) { Toto toto; toto.initData(); toto.printData(); //Display the original 5x5 matrix (first display). std::vector<std::thread> threadList(5); //Initialization of vector of 5 threads. for (int i = 0; i < 5; i++) { //Threads initializationss std::vector<int> vec = toto.getData()[i]; //Get each sub-vectors. threadList.at(i) = std::thread(&Toto::threadTask, toto, vec, i); //Each thread will be attached to a specific vector. } for (int j = 0; j < 5; j++) { threadList.at(j).join(); } toto.printData(); //Second display. getchar(); return (0); } However, in the method threadTask, if I print the variable list[x], the output is correct. I think I can't print the correct data in the main because the printData() call is in the main thread and the display in the threadTask function is correct because the method is executed in its own thread (not the main one). It's strange, it means that all threads created in a parent processes can't modified the data in this parent processes ? I think I forget something in my code. I'm really lost. Does anyone can help me, please ? Thank a lot in advance for your help.

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  • Multithreading - are the multi-core processors really doing parallel processing?

    - by so.very.tired
    Are the modern multi-core processors really doing parallel processing? Like, take for example, Intel's core i7 processors. some of them has #of Cores: 4 and #of Threads: 8 (taken from Intel's specifications pages). If I to write a program (say in Java or C) that has multiple threads of execution, will they really be processed concurrently? My instructor said that "it is not always the case with multi-core processors", but didn't gave to much details. And why do Intel have to specify both #of Cores and #of Threads? Isn't thread just a term that describe a program-related abstraction, unlike "cores" which are actual hardware? ("Every thread runs on different core").

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  • Way to kill python thread from inside thread?

    - by user859434
    I have some python code that currently performs expensive computation by performing the computation in parallel through many threads. For a given time period, many threads are created and started on the fly that share the same code which is explicitly stated within the run method of the thread. My question is how do I stop/kill a thread at the end of its run method? (the run is only called once) I need to do this in order to create more threads for the next batch of computation. #Example class someThread(threading.Thread): def __init__(self): #some init code def run(self): #Explicitly Stated Code without constant loops #Something performed to stop/kill this thread

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  • Threading across multiple files

    - by Zach M.
    My program is reading in files and using thread to compute the highest prime number, when I put a print statement into the getNum() function my numbers are printing out. However, it seems to just lag no matter how many threads I input. Each file has 1 million integers in it. Does anyone see something apparently wrong with my code? Basically the code is giving each thread 1000 integers to check before assigning a new thread. I am still a C noobie and am just learning the ropes of threading. My code is a mess right now because I have been switching things around constantly. #include <stdio.h> #include <stdlib.h> #include <time.h> #include <string.h> #include <pthread.h> #include <math.h> #include <semaphore.h> //Global variable declaration char *file1 = "primes1.txt"; char *file2 = "primes2.txt"; char *file3 = "primes3.txt"; char *file4 = "primes4.txt"; char *file5 = "primes5.txt"; char *file6 = "primes6.txt"; char *file7 = "primes7.txt"; char *file8 = "primes8.txt"; char *file9 = "primes9.txt"; char *file10 = "primes10.txt"; char **fn; //file name variable int numberOfThreads; int *highestPrime = NULL; int fileArrayNum = 0; int loop = 0; int currentFile = 0; sem_t semAccess; sem_t semAssign; int prime(int n)//check for prime number, return 1 for prime 0 for nonprime { int i; for(i = 2; i <= sqrt(n); i++) if(n % i == 0) return(0); return(1); } int getNum(FILE* file) { int number; char* tempS = malloc(20 *sizeof(char)); fgets(tempS, 20, file); tempS[strlen(tempS)-1] = '\0'; number = atoi(tempS); free(tempS);//free memory for later call return(number); } void* findPrimality(void *threadnum) //main thread function to find primes { int tNum = (int)threadnum; int checkNum; char *inUseFile = NULL; int x=1; FILE* file; while(currentFile < 10){ if(inUseFile == NULL){//inUseFIle being used to check if a file is still being read sem_wait(&semAccess);//critical section inUseFile = fn[currentFile]; sem_post(&semAssign); file = fopen(inUseFile, "r"); while(!feof(file)){ if(x % 1000 == 0 && tNum !=1){ //go for 1000 integers and then wait sem_wait(&semAssign); } checkNum = getNum(file); /* * * * * I think the issue is here * * * */ if(checkNum > highestPrime[tNum]){ if(prime(checkNum)){ highestPrime[tNum] = checkNum; } } x++; } fclose(file); inUseFile = NULL; } currentFile++; } } int main(int argc, char* argv[]) { if(argc != 2){ //checks for number of arguements being passed printf("To many ARGS\n"); return(-1); } else{//Sets thread cound to user input checking for correct number of threads numberOfThreads = atoi(argv[1]); if(numberOfThreads < 1 || numberOfThreads > 10){ printf("To many threads entered\n"); return(-1); } time_t preTime, postTime; //creating time variables int i; fn = malloc(10 * sizeof(char*)); //create file array and initialize fn[0] = file1; fn[1] = file2; fn[2] = file3; fn[3] = file4; fn[4] = file5; fn[5] = file6; fn[6] = file7; fn[7] = file8; fn[8] = file9; fn[9] = file10; sem_init(&semAccess, 0, 1); //initialize semaphores sem_init(&semAssign, 0, numberOfThreads); highestPrime = malloc(numberOfThreads * sizeof(int)); //create an array to store each threads highest number for(loop = 0; loop < numberOfThreads; loop++){//set initial values to 0 highestPrime[loop] = 0; } pthread_t calculationThread[numberOfThreads]; //thread to do the work preTime = time(NULL); //start the clock for(i = 0; i < numberOfThreads; i++){ pthread_create(&calculationThread[i], NULL, findPrimality, (void *)i); } for(i = 0; i < numberOfThreads; i++){ pthread_join(calculationThread[i], NULL); } for(i = 0; i < numberOfThreads; i++){ printf("this is a prime number: %d \n", highestPrime[i]); } postTime= time(NULL); printf("Wall time: %ld seconds\n", (long)(postTime - preTime)); } } Yes I am trying to find the highest number over all. So I have made some head way the last few hours, rescucturing the program as spudd said, currently I am getting a segmentation fault due to my use of structures, I am trying to save the largest individual primes in the struct while giving them the right indices. This is the revised code. So in short what the first thread is doing is creating all the threads and giving them access points to a very large integer array which they will go through and find prime numbers, I want to implement semaphores around the while loop so that while they are executing every 2000 lines or the end they update a global prime number. #include <stdio.h> #include <stdlib.h> #include <time.h> #include <string.h> #include <pthread.h> #include <math.h> #include <semaphore.h> //Global variable declaration char *file1 = "primes1.txt"; char *file2 = "primes2.txt"; char *file3 = "primes3.txt"; char *file4 = "primes4.txt"; char *file5 = "primes5.txt"; char *file6 = "primes6.txt"; char *file7 = "primes7.txt"; char *file8 = "primes8.txt"; char *file9 = "primes9.txt"; char *file10 = "primes10.txt"; int numberOfThreads; int entries[10000000]; int entryIndex = 0; int fileCount = 0; char** fileName; int largestPrimeNumber = 0; //Register functions int prime(int n); int getNum(FILE* file); void* findPrimality(void *threadNum); void* assign(void *num); typedef struct package{ int largestPrime; int startingIndex; int numberCount; }pack; //Beging main code block int main(int argc, char* argv[]) { if(argc != 2){ //checks for number of arguements being passed printf("To many threads!!\n"); return(-1); } else{ //Sets thread cound to user input checking for correct number of threads numberOfThreads = atoi(argv[1]); if(numberOfThreads < 1 || numberOfThreads > 10){ printf("To many threads entered\n"); return(-1); } int threadPointer[numberOfThreads]; //Pointer array to point to entries time_t preTime, postTime; //creating time variables int i; fileName = malloc(10 * sizeof(char*)); //create file array and initialize fileName[0] = file1; fileName[1] = file2; fileName[2] = file3; fileName[3] = file4; fileName[4] = file5; fileName[5] = file6; fileName[6] = file7; fileName[7] = file8; fileName[8] = file9; fileName[9] = file10; FILE* filereader; int currentNum; for(i = 0; i < 10; i++){ filereader = fopen(fileName[i], "r"); while(!feof(filereader)){ char* tempString = malloc(20 *sizeof(char)); fgets(tempString, 20, filereader); tempString[strlen(tempString)-1] = '\0'; entries[entryIndex] = atoi(tempString); entryIndex++; free(tempString); } } //sem_init(&semAccess, 0, 1); //initialize semaphores //sem_init(&semAssign, 0, numberOfThreads); time_t tPre, tPost; pthread_t coordinate; tPre = time(NULL); pthread_create(&coordinate, NULL, assign, (void**)numberOfThreads); pthread_join(coordinate, NULL); tPost = time(NULL); } } void* findPrime(void* pack_array) { pack* currentPack= pack_array; int lp = currentPack->largestPrime; int si = currentPack->startingIndex; int nc = currentPack->numberCount; int i; int j = 0; for(i = si; i < nc; i++){ while(j < 2000 || i == (nc-1)){ if(prime(entries[i])){ if(entries[i] > lp) lp = entries[i]; } j++; } } return (void*)currentPack; } void* assign(void* num) { int y = (int)num; int i; int count = 10000000/y; int finalCount = count + (10000000%y); int sIndex = 0; pack pack_array[(int)num]; pthread_t workers[numberOfThreads]; //thread to do the workers for(i = 0; i < y; i++){ if(i == (y-1)){ pack_array[i].largestPrime = 0; pack_array[i].startingIndex = sIndex; pack_array[i].numberCount = finalCount; } pack_array[i].largestPrime = 0; pack_array[i].startingIndex = sIndex; pack_array[i].numberCount = count; pthread_create(&workers[i], NULL, findPrime, (void *)&pack_array[i]); sIndex += count; } for(i = 0; i< y; i++) pthread_join(workers[i], NULL); } //Functions int prime(int n)//check for prime number, return 1 for prime 0 for nonprime { int i; for(i = 2; i <= sqrt(n); i++) if(n % i == 0) return(0); return(1); }

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  • How to fix basicHttpBinding in WCF when using multiple proxy clients?

    - by Hemant
    [Question seems a little long but please have patience. It has sample source to explain the problem.] Consider following code which is essentially a WCF host: [ServiceContract (Namespace = "http://www.mightycalc.com")] interface ICalculator { [OperationContract] int Add (int aNum1, int aNum2); } [ServiceBehavior (InstanceContextMode = InstanceContextMode.PerCall)] class Calculator: ICalculator { public int Add (int aNum1, int aNum2) { Thread.Sleep (2000); //Simulate a lengthy operation return aNum1 + aNum2; } } class Program { static void Main (string[] args) { try { using (var serviceHost = new ServiceHost (typeof (Calculator))) { var httpBinding = new BasicHttpBinding (BasicHttpSecurityMode.None); serviceHost.AddServiceEndpoint (typeof (ICalculator), httpBinding, "http://172.16.9.191:2221/calc"); serviceHost.Open (); Console.WriteLine ("Service is running. ENJOY!!!"); Console.WriteLine ("Type 'stop' and hit enter to stop the service."); Console.ReadLine (); if (serviceHost.State == CommunicationState.Opened) serviceHost.Close (); } } catch (Exception e) { Console.WriteLine (e); Console.ReadLine (); } } } Also the WCF client program is: class Program { static int COUNT = 0; static Timer timer = null; static void Main (string[] args) { var threads = new Thread[10]; for (int i = 0; i < threads.Length; i++) { threads[i] = new Thread (Calculate); threads[i].Start (null); } timer = new Timer (o => Console.WriteLine ("Count: {0}", COUNT), null, 1000, 1000); Console.ReadLine (); timer.Dispose (); } static void Calculate (object state) { var c = new CalculatorClient ("BasicHttpBinding_ICalculator"); c.Open (); while (true) { try { var sum = c.Add (2, 3); Interlocked.Increment (ref COUNT); } catch (Exception ex) { Console.WriteLine ("Error on thread {0}: {1}", Thread.CurrentThread.Name, ex.GetType ()); break; } } c.Close (); } } Basically, I am creating 10 proxy clients and then repeatedly calling Add service method on separate threads. Now if I run both applications and observe opened TCP connections using netstat, I find that: If both client and server are running on same machine, number of tcp connections are equal to number of proxy objects. It means all requests are being served in parallel. Which is good. If I run server on a separate machine, I observed that maximum 2 TCP connections are opened regardless of the number of proxy objects I create. Only 2 requests run in parallel. It hurts the processing speed badly. If I switch to net.tcp binding, everything works fine (a separate TCP connection for each proxy object even if they are running on different machines). I am very confused and unable to make the basicHttpBinding use more TCP connections. I know it is a long question, but please help!

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  • WPF vs. WinForms - a Delphi programmer's perspective?

    - by Robert Oschler
    I have read most of the major threads on WPF vs. WinForms and I find myself stuck in the unfortunate ambivalence you can fall into when deciding between the tried and true previous tech (Winforms), and it's successor (WPF). I am a veteran Delphi programmer of many years that is finally making the jump to C#. My fellow Delphi programmers out there will understand that I am excited to know that Anders Hejlsberg, of Delphi fame, was the architect behind C#. I have a strong addiction to Delphi's VCL custom components, especially those involved in making multi-step Wizards and components that act as a container for child components. With that background, I am hoping that those of you that switched from Delphi to C# can help me with my WinForms vs. WPF decision for writing my initial applications. Note, I am very impatient when coding and things like full fledged auto-complete and proper debugger support can make or break a project for me, including being able to find readily available information on API features and calls and even more so, workarounds for bugs. The SO threads and comments in the early 2009 date range give me great concern over WPF when it comes to potential frustrations that could mar my C# UI development coding. On the other hand, spending an inordinate amount of time learning an API tech that is, even if it is not abandoned, soon to be replaced (WinForms), is equally troubling and I do find the GPU support in WPF tantalizing. Hence my ambivalence. Since I haven't learned either tech yet I have a rare opportunity to get a fresh start and not have to face the big "unlearning" curve I've seen people mention in various threads when a WinForms programmer makes the move to WPF. On the other hand, if using WPF will just be too frustrating or have other major negative consequences for an impatient RAD developer like myself, then I'll just stick with WinForms until WPF reaches the same level of support and ease of use. To give you a concrete example into my psychology as a programmer, I used VB and subsequently Delphi to completely avoid altogether the very real pain of coding with MFC, a Windows UI library that many developers suffered through while developing early Windows apps. I have never regretted my luck in avoiding MFC. It would also be comforting to know if Anders Hejlsberg had a hand in the architecture of WPF and/or WinForms, and if there are any disparities in the creative vision and ease of use embodied in either code base. Finally, for the Delphi programmers again, let me know how much "IDE schock" I'm in for when using WPF as opposed to WinForms, especially when it comes to debugger support. Any job market comments updated for 2011 would be appreciated too. -- roschler

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  • WPF vs. WinForms - a Delphi programmer's perspective?

    - by Robert Oschler
    Hello all. I have read most of the major threads on WPF vs. WinForms and I find myself stuck in the unfortunate ambivalence you can fall into when deciding between the tried and true previous tech (Winforms), and it's successor (WPF). I am a veteran Delphi programmer of many years that is finally making the jump to C#. My fellow Delphi programmers out there will understand that I am excited to know that Anders Hejlsberg, of Delphi fame, was the architect behind C#. I have a strong addiction to Delphi's VCL custom components, especially those involved in making multi-step Wizards and components that act as a container for child components. With that background, I am hoping that those of you that switched from Delphi to C# can help me with my WinForms vs. WPF decision for writing my initial applications. Note, I am very impatient when coding and things like full fledged auto-complete and proper debugger support can make or break a project for me, including being able to find readily available information on API features and calls and even more so, workarounds for bugs. The SO threads and comments in the early 2009 date range give me great concern over WPF when it comes to potential frustrations that could mar my C# UI development coding. On the other hand, spending an inordinate amount of time learning an API tech that is, even if it is not abandoned, soon to be replaced (WinForms), is equally troubling and I do find the GPU support in WPF tantalizing. Hence my ambivalence. Since I haven't learned either tech yet I have a rare opportunity to get a fresh start and not have to face the big "unlearning" curve I've seen people mention in various threads when a WinForms programmer makes the move to WPF. On the other hand, if using WPF will just be too frustrating or have other major negative consequences for an impatient RAD developer like myself, then I'll just stick with WinForms until WPF reaches the same level of support and ease of use. To give you a concrete example into my psychology as a programmer, I used VB and subsequently Delphi to completely avoid altogether the very real pain of coding with MFC, a Windows UI library that many developers suffered through while developing early Windows apps. I have never regretted my luck in avoiding MFC. It would also be comforting to know if Anders Hejlsberg had a hand in the architecture of WPF and/or WinForms, and if there are any disparities in the creative vision and ease of use embodied in either code base. Finally, for the Delphi programmers again, let me know how much "IDE schock" I'm in for when using WPF as opposed to WinForms, especially when it comes to debugger support. Any job market comments updated for 2011 would be appreciated too. -- roschler

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  • What's up with LDoms: Part 1 - Introduction & Basic Concepts

    - by Stefan Hinker
    LDoms - the correct name is Oracle VM Server for SPARC - have been around for quite a while now.  But to my surprise, I get more and more requests to explain how they work or to give advise on how to make good use of them.  This made me think that writing up a few articles discussing the different features would be a good idea.  Now - I don't intend to rewrite the LDoms Admin Guide or to copy and reformat the (hopefully) well known "Beginners Guide to LDoms" by Tony Shoumack from 2007.  Those documents are very recommendable - especially the Beginners Guide, although based on LDoms 1.0, is still a good place to begin with.  However, LDoms have come a long way since then, and I hope to contribute to their adoption by discussing how they work and what features there are today.  In this and the following posts, I will use the term "LDoms" as a common abbreviation for Oracle VM Server for SPARC, just because it's a lot shorter and easier to type (and presumably, read). So, just to get everyone on the same baseline, lets briefly discuss the basic concepts of virtualization with LDoms.  LDoms make use of a hypervisor as a layer of abstraction between real, physical hardware and virtual hardware.  This virtual hardware is then used to create a number of guest systems which each behave very similar to a system running on bare metal:  Each has its own OBP, each will install its own copy of the Solaris OS and each will see a certain amount of CPU, memory, disk and network resources available to it.  Unlike some other type 1 hypervisors running on x86 hardware, the SPARC hypervisor is embedded in the system firmware and makes use both of supporting functions in the sun4v SPARC instruction set as well as the overall CPU architecture to fulfill its function. The CMT architecture of the supporting CPUs (T1 through T4) provide a large number of cores and threads to the OS.  For example, the current T4 CPU has eight cores, each running 8 threads, for a total of 64 threads per socket.  To the OS, this looks like 64 CPUs.  The SPARC hypervisor, when creating guest systems, simply assigns a certain number of these threads exclusively to one guest, thus avoiding the overhead of having to schedule OS threads to CPUs, as do typical x86 hypervisors.  The hypervisor only assigns CPUs and then steps aside.  It is not involved in the actual work being dispatched from the OS to the CPU, all it does is maintain isolation between different guests. Likewise, memory is assigned exclusively to individual guests.  Here,  the hypervisor provides generic mappings between the physical hardware addresses and the guest's views on memory.  Again, the hypervisor is not involved in the actual memory access, it only maintains isolation between guests. During the inital setup of a system with LDoms, you start with one special domain, called the Control Domain.  Initially, this domain owns all the hardware available in the system, including all CPUs, all RAM and all IO resources.  If you'd be running the system un-virtualized, this would be what you'd be working with.  To allow for guests, you first resize this initial domain (also called a primary domain in LDoms speak), assigning it a small amount of CPU and memory.  This frees up most of the available CPU and memory resources for guest domains.  IO is a little more complex, but very straightforward.  When LDoms 1.0 first came out, the only way to provide IO to guest systems was to create virtual disk and network services and attach guests to these services.  In the meantime, several different ways to connect guest domains to IO have been developed, the most recent one being SR-IOV support for network devices released in version 2.2 of Oracle VM Server for SPARC. I will cover these more advanced features in detail later.  For now, lets have a short look at the initial way IO was virtualized in LDoms: For virtualized IO, you create two services, one "Virtual Disk Service" or vds, and one "Virtual Switch" or vswitch.  You can, of course, also create more of these, but that's more advanced than I want to cover in this introduction.  These IO services now connect real, physical IO resources like a disk LUN or a networt port to the virtual devices that are assigned to guest domains.  For disk IO, the normal case would be to connect a physical LUN (or some other storage option that I'll discuss later) to one specific guest.  That guest would be assigned a virtual disk, which would appear to be just like a real LUN to the guest, while the IO is actually routed through the virtual disk service down to the physical device.  For network, the vswitch acts very much like a real, physical ethernet switch - you connect one physical port to it for outside connectivity and define one or more connections per guest, just like you would plug cables between a real switch and a real system. For completeness, there is another service that provides console access to guest domains which mimics the behavior of serial terminal servers. The connections between the virtual devices on the guest's side and the virtual IO services in the primary domain are created by the hypervisor.  It uses so called "Logical Domain Channels" or LDCs to create point-to-point connections between all of these devices and services.  These LDCs work very similar to high speed serial connections and are configured automatically whenever the Control Domain adds or removes virtual IO. To see all this in action, now lets look at a first example.  I will start with a newly installed machine and configure the control domain so that it's ready to create guest systems. In a first step, after we've installed the software, let's start the virtual console service and downsize the primary domain.  root@sun # ldm list NAME STATE FLAGS CONS VCPU MEMORY UTIL UPTIME primary active -n-c-- UART 512 261632M 0.3% 2d 13h 58m root@sun # ldm add-vconscon port-range=5000-5100 \ primary-console primary root@sun # svcadm enable vntsd root@sun # svcs vntsd STATE STIME FMRI online 9:53:21 svc:/ldoms/vntsd:default root@sun # ldm set-vcpu 16 primary root@sun # ldm set-mau 1 primary root@sun # ldm start-reconf primary root@sun # ldm set-memory 7680m primary root@sun # ldm add-config initial root@sun # shutdown -y -g0 -i6 So what have I done: I've defined a range of ports (5000-5100) for the virtual network terminal service and then started that service.  The vnts will later provide console connections to guest systems, very much like serial NTS's do in the physical world. Next, I assigned 16 vCPUs (on this platform, a T3-4, that's two cores) to the primary domain, freeing the rest up for future guest systems.  I also assigned one MAU to this domain.  A MAU is a crypto unit in the T3 CPU.  These need to be explicitly assigned to domains, just like CPU or memory.  (This is no longer the case with T4 systems, where crypto is always available everywhere.) Before I reassigned the memory, I started what's called a "delayed reconfiguration" session.  That avoids actually doing the change right away, which would take a considerable amount of time in this case.  Instead, I'll need to reboot once I'm all done.  I've assigned 7680MB of RAM to the primary.  That's 8GB less the 512MB which the hypervisor uses for it's own private purposes.  You can, depending on your needs, work with less.  I'll spend a dedicated article on sizing, discussing the pros and cons in detail. Finally, just before the reboot, I saved my work on the ILOM, to make this configuration available after a powercycle of the box.  (It'll always be available after a simple reboot, but the ILOM needs to know the configuration of the hypervisor after a power-cycle, before the primary domain is booted.) Now, lets create a first disk service and a first virtual switch which is connected to the physical network device igb2. We will later use these to connect virtual disks and virtual network ports of our guest systems to real world storage and network. root@sun # ldm add-vds primary-vds root@sun # ldm add-vswitch net-dev=igb2 switch-primary primary You are free to choose whatever names you like for the virtual disk service and the virtual switch.  I strongly recommend that you choose names that make sense to you and describe the function of each service in the context of your implementation.  For the vswitch, for example, you could choose names like "admin-vswitch" or "production-network" etc. This already concludes the configuration of the control domain.  We've freed up considerable amounts of CPU and RAM for guest systems and created the necessary infrastructure - console, vts and vswitch - so that guests systems can actually interact with the outside world.  The system is now ready to create guests, which I'll describe in the next section. For further reading, here are some recommendable links: The LDoms 2.2 Admin Guide The "Beginners Guide to LDoms" The LDoms Information Center on MOS LDoms on OTN

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  • Haskell vs Erlang for web services

    - by Zachary K
    I am looking to start an experimental project using a functional language and am trying to decide beween Erlang and Haskell, and both have some points that I really like. I like Haskell's strong type system and purity. I have a feeling it will make it easier to write really reliable code. And I think that the power of haskell will make some of what I want to do much easier. On the minus side I get the feeling that some of the Frameworks for doing web stuff on Haskell such as Yesod are not as advanced as their Erlang counter parts. I rather like the Erlang approach to threads and to fault tollerence. I have a feeling that the scalability of Erlang could be a major plus. Which leeds to to my question, what has people's exerience been in implementing web application backends in both Haskell and Erlang. Are there packages for Haskell to provide some of the lightweight threads and actors that one has in Erlang?

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  • IBM "per core" comparisons for SPECjEnterprise2010

    - by jhenning
    I recently stumbled upon a blog entry from Roman Kharkovski (an IBM employee) comparing some SPECjEnterprise2010 results for IBM vs. Oracle. Mr. Kharkovski's blog claims that SPARC delivers half the transactions per core vs. POWER7. Prior to any argument, I should say that my predisposition is to like Mr. Kharkovski, because he says that his blog is intended to be factual; that the intent is to try to avoid marketing hype and FUD tactic; and mostly because he features a picture of himself wearing a bike helmet (me too). Therefore, in a spirit of technical argument, rather than FUD fight, there are a few areas in his comparison that should be discussed. Scaling is not free For any benchmark, if a small system scores 13k using quantity R1 of some resource, and a big system scores 57k using quantity R2 of that resource, then, sure, it's tempting to divide: is  13k/R1 > 57k/R2 ? It is tempting, but not necessarily educational. The problem is that scaling is not free. Building big systems is harder than building small systems. Scoring  13k/R1  on a little system provides no guarantee whatsoever that one can sustain that ratio when attempting to handle more than 4 times as many users. Choosing the denominator radically changes the picture When ratios are used, one can vastly manipulate appearances by the choice of denominator. In this case, lots of choices are available for the resource to be compared (R1 and R2 above). IBM chooses to put cores in the denominator. Mr. Kharkovski provides some reasons for that choice in his blog entry. And yet, it should be noted that the very concept of a core is: arbitrary: not necessarily comparable across vendors; fluid: modern chips shift chip resources in response to load; and invisible: unless you have a microscope, you can't see it. By contrast, one can actually see processor chips with the naked eye, and they are a bit easier to count. If we put chips in the denominator instead of cores, we get: 13161.07 EjOPS / 4 chips = 3290 EjOPS per chip for IBM vs 57422.17 EjOPS / 16 chips = 3588 EjOPS per chip for Oracle The choice of denominator makes all the difference in the appearance. Speaking for myself, dividing by chips just seems to make more sense, because: I can see chips and count them; and I can accurately compare the number of chips in my system to the count in some other vendor's system; and Tthe probability of being able to continue to accurately count them over the next 10 years of microprocessor development seems higher than the probability of being able to accurately and comparably count "cores". SPEC Fair use requirements Speaking as an individual, not speaking for SPEC and not speaking for my employer, I wonder whether Mr. Kharkovski's blog article, taken as a whole, meets the requirements of the SPEC Fair Use rule www.spec.org/fairuse.html section I.D.2. For example, Mr. Kharkovski's footnote (1) begins Results from http://www.spec.org as of 04/04/2013 Oracle SUN SPARC T5-8 449 EjOPS/core SPECjEnterprise2010 (Oracle's WLS best SPECjEnterprise2010 EjOPS/core result on SPARC). IBM Power730 823 EjOPS/core (World Record SPECjEnterprise2010 EJOPS/core result) The questionable tactic, from a Fair Use point of view, is that there is no such metric at the designated location. At www.spec.org, You can find the SPEC metric 57422.17 SPECjEnterprise2010 EjOPS for Oracle and You can also find the SPEC metric 13161.07 SPECjEnterprise2010 EjOPS for IBM. Despite the implication of the footnote, you will not find any mention of 449 nor anything that says 823. SPEC says that you can, under its fair use rule, derive your own values; but it emphasizes: "The context must not give the appearance that SPEC has created or endorsed the derived value." Substantiation and transparency Although SPEC disclaims responsibility for non-SPEC information (section I.E), it says that non-SPEC data and methods should be accurate, should be explained, should be substantiated. Unfortunately, it is difficult or impossible for the reader to independently verify the pricing: Were like units compared to like (e.g. list price to list price)? Were all components (hw, sw, support) included? Were all fees included? Note that when tpc.org shows IBM pricing, there are often items such as "PROCESSOR ACTIVATION" and "MEMORY ACTIVATION". Without the transparency of a detailed breakdown, the pricing claims are questionable. T5 claim for "Fastest Processor" Mr. Kharkovski several times questions Oracle's claim for fastest processor, writing You see, when you publish industry benchmarks, people may actually compare your results to other vendor's results. Well, as we performance people always say, "it depends". If you believe in performance-per-core as the primary way of looking at the world, then yes, the POWER7+ is impressive, spending its chip resources to support up to 32 threads (8 cores x 4 threads). Or, it just might be useful to consider performance-per-chip. Each SPARC T5 chip allows 128 hardware threads to be simultaneously executing (16 cores x 8 threads). The Industry Standard Benchmark that focuses specifically on processor chip performance is SPEC CPU2006. For this very well known and popular benchmark, SPARC T5: provides better performance than both POWER7 and POWER7+, for 1 chip vs. 1 chip, for 8 chip vs. 8 chip, for integer (SPECint_rate2006) and floating point (SPECfp_rate2006), for Peak tuning and for Base tuning. For example, at the 8-chip level, integer throughput (SPECint_rate2006) is: 3750 for SPARC 2170 for POWER7+. You can find the details at the March 2013 BestPerf CPU2006 page SPEC is a trademark of the Standard Performance Evaluation Corporation, www.spec.org. The two specific results quoted for SPECjEnterprise2010 are posted at the URLs linked from the discussion. Results for SPEC CPU2006 were verified at spec.org 1 July 2013, and can be rechecked here.

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  • Why lock statements don't scale

    - by Alex.Davies
    We are going to have to stop using lock statements one day. Just like we had to stop using goto statements. The problem is similar, they're pretty easy to follow in small programs, but code with locks isn't composable. That means that small pieces of program that work in isolation can't necessarily be put together and work together. Of course actors scale fine :) Why lock statements don't scale as software gets bigger Deadlocks. You have a program with lots of threads picking up lots of locks. You already know that if two of your threads both try to pick up a lock that the other already has, they will deadlock. Your program will come to a grinding halt, and there will be fire and brimstone. "Easy!" you say, "Just make sure all the threads pick up the locks in the same order." Yes, that works. But you've broken composability. Now, to add a new lock to your code, you have to consider all the other locks already in your code and check that they are taken in the right order. Algorithm buffs will have noticed this approach means it takes quadratic time to write a program. That's bad. Why lock statements don't scale as hardware gets bigger Memory bus contention There's another headache, one that most programmers don't usually need to think about, but is going to bite us in a big way in a few years. Locking needs exclusive use of the entire system's memory bus while taking out the lock. That's not too bad for a single or dual-core system, but already for quad-core systems it's a pretty large overhead. Have a look at this blog about the .NET 4 ThreadPool for some numbers and a weird analogy (see the author's comment). Not too bad yet, but I'm scared my 1000 core machine of the future is going to go slower than my machine today! I don't know the answer to this problem yet. Maybe some kind of per-core work queue system with hierarchical work stealing. Definitely hardware support. But what I do know is that using locks specifically prevents any solution to this. We should be abstracting our code away from the details of locks as soon as possible, so we can swap in whatever solution arrives when it does. NAct uses locks at the moment. But my advice is that you code using actors (which do scale well as software gets bigger). And when there's a better way of implementing actors that'll scale well as hardware gets bigger, only NAct needs to work out how to use it, and your program will go fast on it's own.

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  • A Method for Reducing Contention and Overhead in Worker Queues for Multithreaded Java Applications

    - by Janice J. Heiss
    A java.net article, rich in practical resources, by IBM India Labs’ Sathiskumar Palaniappan, Kavitha Varadarajan, and Jayashree Viswanathan, explores the challenge of writing code in a way that that effectively makes use of the resources of modern multicore processors and multiprocessor servers.As the article states: “Many server applications, such as Web servers, application servers, database servers, file servers, and mail servers, maintain worker queues and thread pools to handle large numbers of short tasks that arrive from remote sources. In general, a ‘worker queue’ holds all the short tasks that need to be executed, and the threads in the thread pool retrieve the tasks from the worker queue and complete the tasks. Since multiple threads act on the worker queue, adding tasks to and deleting tasks from the worker queue needs to be synchronized, which introduces contention in the worker queue.” The article goes on to explain ways that developers can reduce contention by maintaining one queue per thread. It also demonstrates a work-stealing technique that helps in effectively utilizing the CPU in multicore systems. Read the rest of the article here.

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  • matplotlib and python multithread file processing

    - by Napseis
    I have a large number of files to process. I have written a script that get, sort and plot the datas I want. So far, so good. I have tested it and it gives the desired result. Then I wanted to do this using multithreading. I have looked into the doc and examples on the internet, and using one thread in my program works fine. But when I use more, at some point I get random matplotlib error, and I suspect some conflict there, even though I use a function with names for the plots, and iI can't see where the problem could be. Here is the whole script should you need more comment, i'll add them. Thank you. #!/usr/bin/python import matplotlib matplotlib.use('GTKAgg') import numpy as np from scipy.interpolate import griddata import matplotlib.pyplot as plt import matplotlib.colors as mcl from matplotlib import rc #for latex import time as tm import sys import threading import Queue #queue in 3.2 and Queue in 2.7 ! import pdb #the debugger rc('text', usetex=True)#for latex map=0 #initialize the map index. It will be use to index the array like this: array[map,[x,y]] time=np.zeros(1) #an array to store the time middle_h=np.zeros((0,3)) #x phi c #for the middle of the box current_file=open("single_void_cyl_periodic_phi_c_middle_h_out",'r') for line in current_file: if line.startswith('# === time'): map+=1 np.append(time,[float(line.strip('# === time '))]) elif line.startswith('#'): pass else: v=np.fromstring(line,dtype=float,sep=' ') middle_h=np.vstack( (middle_h,v[[1,3,4]]) ) current_file.close() middle_h=middle_h.reshape((map,-1,3)) #3d array: map, x, phi,c ##### def load_and_plot(): #will load a map file, and plot it along with the corresponding profile loaded before while not exit_flag: print("fecthing work ...") #try: if not tasks_queue.empty(): map_index=tasks_queue.get() print("----> working on map: %s" %map_index) x,y,zp=np.loadtxt("single_void_cyl_growth_periodic_post_map_"+str(map_index),unpack=True, usecols=[1, 2,3]) for i,el in enumerate(zp): if el<0.: zp[i]=0. xv=np.unique(x) yv=np.unique(y) X,Y= np.meshgrid(xv,yv) Z = griddata((x, y), zp, (X, Y),method='nearest') figure=plt.figure(num=map_index,figsize=(14, 8)) ax1=plt.subplot2grid((2,2),(0,0)) ax1.plot(middle_h[map_index,:,0],middle_h[map_index,:,1],'*b') ax1.grid(True) ax1.axis([-15, 15, 0, 1]) ax1.set_title('Profiles') ax1.set_ylabel(r'$\phi$') ax1.set_xlabel('x') ax2=plt.subplot2grid((2,2),(1,0)) ax2.plot(middle_h[map_index,:,0],middle_h[map_index,:,2],'*r') ax2.grid(True) ax2.axis([-15, 15, 0, 1]) ax2.set_ylabel('c') ax2.set_xlabel('x') ax3=plt.subplot2grid((2,2),(0,1),rowspan=2,aspect='equal') sub_contour=ax3.contourf(X,Y,Z,np.linspace(0,1,11),vmin=0.) figure.colorbar(sub_contour,ax=ax3) figure.savefig('single_void_cyl_'+str(map_index)+'.png') plt.close(map_index) tasks_queue.task_done() else: print("nothing left to do, other threads finishing,sleeping 2 seconds...") tm.sleep(2) # except: # print("failed this time: %s" %map_index+". Sleeping 2 seconds") # tm.sleep(2) ##### exit_flag=0 nb_threads=2 tasks_queue=Queue.Queue() threads_list=[] jobs=list(range(map)) #each job is composed of a map print("inserting jobs in the queue...") for job in jobs: tasks_queue.put(job) print("done") #launch the threads for i in range(nb_threads): working_bee=threading.Thread(target=load_and_plot) working_bee.daemon=True print("starting thread "+str(i)+' ...') threads_list.append(working_bee) working_bee.start() #wait for all tasks to be treated tasks_queue.join() #flip the flag, so the threads know it's time to stop exit_flag=1 for t in threads_list: print("waiting for threads %s to stop..."%t) t.join() print("all threads stopped")

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  • Parallelism implies concurrency but not the other way round right?

    - by Cedric Martin
    I often read that parallelism and concurrency are different things. Very often the answerers/commenters go as far as writing that they're two entirely different things. Yet in my view they're related but I'd like some clarification on that. For example if I'm on a multi-core CPU and manage to divide the computation into x smaller computation (say using fork/join) each running in its own thread, I'll have a program that is both doing parallel computation (because supposedly at any point in time several threads are going to run on several cores) and being concurrent right? While if I'm simply using, say, Java and dealing with UI events and repaints on the Event Dispatch Thread plus running the only thread I created myself, I'll have a program that is concurrent (EDT + GC thread + my main thread etc.) but not parallel. I'd like to know if I'm getting this right and if parallelism (on a "single but multi-cores" system) always implies concurrency or not? Also, are multi-threaded programs running on multi-cores CPU but where the different threads are doing totally different computation considered to be using "parallelism"?

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  • Number crunching algo for learning multithreading?

    - by Austin Henley
    I have never really implemented anything dealing with threads; my only experience with them is reading about them in my undergrad. So I want to change that by writing a program that does some number crunching, but splits it up into several threads. My first ideas for this hopefully simple multithreaded program were: Beal's Conjecture brute force based on my SO question. Bailey-Borwein-Plouffe formula for calculating Pi. Prime number brute force search As you can see I have an interest in math and thought it would be fun to incorporate it into this, rather than coding something such as a server which wouldn't be nearly as fun! But the 3 ideas don't seem very appealing and I have already done some work on them in the past so I was curious if anyone had any ideas in the same spirit as these 3 that I could implement?

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  • Why isn't reflection on the SCJP / OCJP?

    - by Nick Rosencrantz
    I read through Kathy Sierra's SCJP study guide and I will read it again more throughly to improve myself as a Java programmer and be able to take the certification either Java 6 or wait for the Java 7 exam (I'm already employed as Java developer so I'm in no hurry to take the exam.) Now I wonder why reflection is not on the exam? The book it seems covers everything that should be on the exam and AFAIK reflection is at least as important as threads if not more used inpractice since many frameworks use reflection. Do you know why reflection is not part of the SCJP? Do you agree that it's at least important to know reflection as threads? Thanks for any answer

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