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  • What are the limitations of a STA thread in compare to MTA threads ?

    - by Xaqron
    If we make a thread STA like this: Thread.SetApartmentState(STA); then it cannot run code marked with [MTAThread] attribute. We have seen [STAThread] in windows and console applications but I have never seen code with [MTAThread] attribute and don't know which .NET libraries use this attribute. My question is what are the limitations of a thread with apartment state set to STA, in compare to threads with MTA apartment state (natural .NET threads) ?

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  • Can two threads of the same process produce the same GUID?

    - by mark
    Dear ladies and sirs. If two threads in a process generate a new GUID concurrently using .NET API (Guid.NewGuid()) is it possible that the two GUIDs will be identical? Thanks. UPDATE I want to get practical. I know that it is widely assumed that GUIDs are unique for all practical purposes. I am wondering if I can treat GUIDS produced by the different threads of the same process in the same manner.

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  • Is it safe to make GL calls with multiple threads?

    - by user146780
    I was wondering if it was safe to make GL calls with multiple threads. Basically I'm using a GLUtesselator and was wondering if I could divide the objects to draw into 4 and assign a thread to each one. I'm just wondering if this would cause trouble since the tesselator uses callback functions. Can 2 threads run the same callback at the same time as long as that callback does not access ant global variables? Are there also other ways I could optimize OpenGL drawing using multithreading? Thanks

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  • cset shield --kthread on: should I use this?

    - by lori
    I'm reading up on cpu shielding using Alex Tsariounov's cset utility here: https://rt.wiki.kernel.org/index.php/Cpuset_Management_Utility/tutorial In the tutorial I'm finding the wording around migrating kernel threads from having access to all cpus to running only in a certain cpuset a bit ambiguous The tutorial says the following: Some kernel threads can be moved into the unshielded system cpuset as well. These are the threads that are not bound to specific CPUs. If a kernel thread is bound to a specific CPU, then it is generally not a good idea to move that thread to the system set because at worst it may hang the system and at best it will slow the system down significantly. These threads are usually the IRQ threads on a real time Linux kernel, for example, and you may want to not move these kernel threads into system. If you leave them in the root cpuset, then they will have access to all CPUs. The tutorial then goes on to say: However, if your application demands an even "quieter" shield, then you can move all movable kernel threads into the unshielded system set with the following command. [zuul:cpuset-trunk]# cset shield -k on cset: --> activating kthread shielding cset: kthread shield activated, moving 70 tasks into system cpuset... [==================================================]% cset: done I am confused by this final sentence. By using the word however, it seems to suggest that you typically should not move the movable kernel threads into the unshielded system set. Is this the case, or is it safe to move kernel threads which can be moved into a cpuset, thereby preventing them from running on some cpus?

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  • Implement an FTP server (no threads) - how to start?

    - by ironicaldiction
    As a semester project, I have the following specification: Write a simple single threaded ftp server. The ftp server is configurable from a configuration file. The config allows to set the interface (where the server listens), the roots of the served content, transfer log, and database of users and its passwords. The server allows to create a virtual filesystem. By a virtual filesystem, we mean a mapping of a served directory to the real directory on the filesystem. For example, the client tree will look like: /home/user1 maps to /mnt/x/home/user1 /www maps to /var/cache/www /home/user_list.txt maps to /var/ftpclient/user_list.txt The user will see /home/user1 directory and /www directory and the file /home/user_list.txt The course is in C++. The projects to this point have provided a lot of structure, such as a class header file to get you started on the program. My question is this: how can I get started on what seems like quite a massive project (I have 3 weeks to return a working implementation)?

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  • asyncore callbacks launching threads... ok to do?

    - by sbartell
    I'm unfamiliar with asyncore, and have very limited knowledge of asynchronous programming except for a few intro to twisted tutorials. I am most familiar with threads and use them in all my apps. One particular app uses a couchdb database as its interface. This involves longpolling the db looking for changes and updates. The module I use for couchdb is couchdbkit. It uses an asyncore loop to watch for these changes and send them to a callback. So, I figure from this callback is where I launch my worker threads. It seems a bit crude to mix asynchronous and threaded programming. I really like couchdbkit, but would rather not introduce issues into my program. So, my question is, is it safe to fire threads from an async callback? Here's some code... {{{ def dispatch(change): global jobs, db_url # jobs is my queue db = Database(db_url) work_order = db.get(change['id']) # change is an id to the document that changed. # i need to get the actual document (workorder) worker = Worker(work_order, db) # fire the thread jobs.append[worker] worker.start() return main() . . . consumer.wait(cb=dispatch, since=update_seq, timeout=10000) #wait constains the asyncloop. }}}

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  • Should I pass a SqlDataReader by reference or not when passing it out to multiple threads.

    - by deroby
    Hi all, being new to c# I've run into this 'conundrum' when passing around a SqlDataReader between different threads. Without going into too much detail, the idea is to have a main thread fetching data from the database (a large recordset) and then have a helper-task run through this record by record and doing some stuff based upon the contents of this. There is no feedback to the recordset, it simply wades through until no records are left. This works fine, but given the nature of the job at hand it should be possible to have this job spread over different threads (CPUs) to maximize throughput (the order of execution is of no significance). The question then becomes, when I pass this recordset in a SqlDataReader, do I have to use ref or not ? It kind of boils down to the question : if I pass the object around without specifying ref, won't it create new copies in memory and have records processed n times ? Or, don't I risk having the record-position being moved forward while not all fields have been fully read yet ? The latter seems more like a 'data racing' issue and probably is covered by the lock()ing mechanism (or not?). My initial take on the problem was that it doesn't really hurt passing the variable using ref, yet as a colleague put it : "you only need ref when you're doing something wrong" =) Additionally using ref restricts me from applying a Using() construction too which isn't very nice either. I thus create a "basic" project that tackles the same approach but without the ref notation. Tests so far show that it works flawlessly on a Core2Duo (2cpu) using any number of threads, yet I'm still a bit wary... What do you experts think about this ? Use ref or not ? You can find the test-project here as it seems I can't upload it to this question directly ?!? ps: it's just a test-project and I'm new to c#, so please be gentle on me when breaking down the code =P

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  • How to prevent the other threads from accessing a method when one thread is accessing a method?

    - by geeta
    I want to search for a string in 10 files and write the matching lines to a single file. I wrote the matching lines from each file to 10 output files(o/p file1,o/p file2...) and then copied those to a single file using 10 threads. But the output single file has mixed output(one line from o/p file1,another line from o/p file 2 etc...) because its accessed simultaneously by many threads. If I wait for all threads to complete and then write the single file it will be much slower. I want the output file to be written by one thread at a time. What should i do? My source code:(only writing to single file method) public void WriteSingle(File output_file,File final_output) throws IOException { synchronized(output_file){ System.out.println("Writing Single file"); FileOutputStream fo = new FileOutputStream(final_output,true); FileChannel fi = fo.getChannel(); FileInputStream fs = new FileInputStream(output_file); FileChannel fc = fs.getChannel(); int maxCount = (64 * 1024 * 1024) - (32 * 1024); long size = fc.size(); long position = 0; while (position < size) { position += fc.transferTo(position, maxCount, fi); } } }

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  • Why aren't my threads start at the same time? Java

    - by Ada
    Hi, I have variable number of threads which are used for parallel downloading. I used this, for(int i = 0; i< sth; i++){ thrList.add(new myThread (parameters)); thrList.get(i).start(); thrList.get(i).join(); } I don't know why but they wait for each other to complete. When using threads, I am supposed get mixed print outs, since right then there are several threads running that code. However, when I print them out, they are always in order and one thread waits for the previous one to finish first. I only want them to join the main thread, not wait for each other. I noticed that when I measured time while downloading in parallel. How can I fix this? Why are they doing it in order? In my .java, there is MyThread class with run and there is Downloader class with static methods and variables. Would they be the cause of this? The static methods and variables? How can I fix this problem?

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  • configuring JRun

    - by Lucien
    We are running JRun 4 and have lots of crashes. I am trying to understand where the problems are coming from and have modified the jrun.xml file to enable metrics logging. This is what I'm seeing... 01/06 15:07:27 metrics Web threads (busy/total/delayed): 2/100/0 Sessions: 0 Total Memory=70720 Free=7464 01/06 15:08:27 metrics Web threads (busy/total/delayed): 1/100/0 Sessions: 0 Total Memory=66944 Free=9199 01/06 15:09:27 metrics Web threads (busy/total/delayed): 3/100/0 Sessions: 0 Total Memory=67456 Free=9644 01/06 15:10:27 metrics Web threads (busy/total/delayed): 3/100/0 Sessions: 0 Total Memory=63360 Free=8368 The book I've been reading (Adobe Coldfusion Anthology, Apress) suggests the "busy" number is the free memory in MB. The Adobe documentation says it's "Threads currently running". Which is correct? Also, what does all this mean? If I'm reading it correctly, I have 100 total threads, and 3 busy ones. So what are the other 97 threads doing if they are neither busy nor delayed?

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  • groovy thread for urls

    - by Srinath
    I wrote logic for testing urls using threads. This works good for less number of urls and failing with more than 400 urls to check . class URL extends Thread{ def valid def url URL( url ) { this.url = url } void run() { try { def connection = url.toURL().openConnection() connection.setConnectTimeout(10000) if(connection.responseCode == 200 ){ valid = Boolean.TRUE }else{ valid = Boolean.FALSE } } catch ( Exception e ) { valid = Boolean.FALSE } } } def threads = []; urls.each { ur - def reader = new URL(ur) reader.start() threads.add(reader); } while (threads.size() 0) { for(int i =0; i < threads.size();i++) { def tr = threads.get(i); if (!tr.isAlive()) { if(tr.valid == true){ threads.remove(i); i--; }else{ threads.remove(i); i--; } } } Could any one please tell me how to optimize the logic and where i was going wrong . thanks in advance.

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  • How to safely operate on parameters in threads, using C++ & Pthreads?

    - by ChrisCphDK
    Hi. I'm having some trouble with a program using pthreads, where occassional crashes occur, that could be related to how the threads operate on data So I have some basic questions about how to program using threads, and memory layout: Assume that a public class function performs some operations on some strings, and returns the result as a string. The prototype of the function could be like this: std::string SomeClass::somefunc(const std::string &strOne, const std::string &strTwo) { //Error checking of strings have been omitted std::string result = strOne.substr(0,5) + strTwo.substr(0,5); return result; } Is it correct to assume that strings, being dynamic, are stored on the heap, but that a reference to the string is allocated on the stack at runtime? Stack: [Some mem addr] pointer address to where the string is on the heap Heap: [Some mem addr] memory allocated for the initial string which may grow or shrink To make the function thread safe, the function is extended with the following mutex (which is declared as private in the "SomeClass") locking: std::string SomeClass::somefunc(const std::string &strOne, const std::string &strTwo) { pthread_mutex_lock(&someclasslock); //Error checking of strings have been omitted std::string result = strOne.substr(0,5) + strTwo.substr(0,5); pthread_mutex_unlock(&someclasslock); return result; } Is this a safe way of locking down the operations being done on the strings (all three), or could a thread be stopped by the scheduler in the following cases, which I'd assume would mess up the intended logic: a. Right after the function is called, and the parameters: strOne & strTwo have been set in the two reference pointers that the function has on the stack, the scheduler takes away processing time for the thread and lets a new thread in, which overwrites the reference pointers to the function, which then again gets stopped by the scheduler, letting the first thread back in? b. Can the same occur with the "result" string: the first string builds the result, unlocks the mutex, but before returning the scheduler lets in another thread which performs all of it's work, overwriting the result etc. Or are the reference parameters / result string being pushed onto the stack while another thread is doing performing it's task? Is the safe / correct way of doing this in threads, and "returning" a result, to pass a reference to a string that will be filled with the result instead: void SomeClass::somefunc(const std::string &strOne, const std::string &strTwo, std::string result) { pthread_mutex_lock(&someclasslock); //Error checking of strings have been omitted result = strOne.substr(0,5) + strTwo.substr(0,5); pthread_mutex_unlock(&someclasslock); } The intended logic is that several objects of the "SomeClass" class creates new threads and passes objects of themselves as parameters, and then calls the function: "someFunc": int SomeClass::startNewThread() { pthread_attr_t attr; pthread_t pThreadID; if(pthread_attr_init(&attr) != 0) return -1; if(pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_DETACHED) != 0) return -2; if(pthread_create(&pThreadID, &attr, proxyThreadFunc, this) != 0) return -3; if(pthread_attr_destroy(&attr) != 0) return -4; return 0; } void* proxyThreadFunc(void* someClassObjPtr) { return static_cast<SomeClass*> (someClassObjPtr)->somefunc("long string","long string"); } Sorry for the long description. But I hope the questions and intended purpose is clear, if not let me know and I'll elaborate. Best regards. Chris

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  • Thread Synchronization and Synchronization Primitives

    When considering synchronization in an application, the decision truly depends on what the application and its worker threads are going to do. I would use synchronization if two or more threads could possibly manipulate the same instance of an object at the same time. An example of this in C# can be demonstrated through the use of storing data in a static object. A static object is initialized once per application and the data within the object can be accessed by all threads. I would use the synchronization primitives to prevent any data from being manipulated by multiple threads simultaneously. This would reduce any data corruption from occurring within the object. On the other hand if all the threads used non static objects and were independent of the other tasks there would be no need to use synchronization. Synchronization Primitives in C#: Basic Blocking Locking Signaling Non-Blocking Synchronization Constructs The Basic Blocking methods include Sleep, Join, and Task.Wait.  These methods force threads to wait until other threads have completed. In addition, these methods can also force a thread to wait a set amount of time before continuing to work.   The Locking primitive prevents a thread from entering a critical section of code while another thread is in the same critical section.  If another thread attempts to enter a locked code, it will wait, until the code block is released. The Signaling primitive allows a thread to temporarily pause work until receiving a notification from another thread that it is ok to continue working. The Signaling primitive removes the need for polling.The Non-Blocking Synchronization Constructs protect access to a common field by calling upon processor primitives.

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  • How can I save state from script in a multithreaded engine?

    - by Peter Ren
    We are building a multithreaded game engine and we've encountered some problems as described below. The engine have 3 threads in total: script, render, and audio. Each frame, we update these 3 threads simultaneously. As these threads updating themselves, they produce some tasks and put them into a public storage area. As all the threads finish their update, each thread go and copy the tasks for themselves one by one. After all the threads finish their task copying, we make the threads process those tasks and update these threads simultaneously as described before. So this is the general idea of the task schedule part of our engine. Ok, well, all the task schedule part work well, but here's the problem: For the simplest, I'll take Camera as an example: local oldPos = camera:getPosition() -- ( 0, 0, 0 ) camera:setPosition( 1, 1, 1 ) -- Won't work now, cuz the render thread will process the task at the beginning of the next frame local newPos = camera:getPosition() -- Still ( 0, 0, 0 ) So that's the problem: If you intend to change a property of an object in another thread, you have to wait until that thread process this property-changing message. As a result, what you get from the object is still the information in the last frame. So, is there a way to solve this problem? Or are we build the task schedule part in a wrong way? Thanks for your answers :)

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  • Best way to fetch data from a single database table with multiple threads?

    - by Ravi Bhatt
    Hi, we have a system where we collect data every second on user activity on multiple web sites. we dump that data into a database X (say MS SQL Server). we now need to fetch data from this single table from daatbase X and insert into database Y (say mySql). we want to fetch time based data from database X through multiple threads so that we fetch as fast as we can. Once fetched and stored in database Y, we will delete data from database X. Are there any best practices on this sort of design? any specific things to take care on table design like sharing or something? Are there any other things that we need to take care to make sure we fetch it as fast as we can from threads running on multiple machines? Thanks in advance! Ravi

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  • Why does Python's math.factorial not play nice with threads?

    - by W1N9Zr0
    Why does math.factorial act so weird in a thread? Here is an example, it creates three threads: thread that just sleeps for a while thread that increments an int for a while thread that does math.factorial on a large number. It calls start on the threads, then join with a timeout The sleep and spin threads work as expected and return from start right away, and then sit in the join for the timeout. The factorial thread on the other hand does not return from start until it runs to the end! import sys from threading import Thread from time import sleep, time from math import factorial # Helper class that stores a start time to compare to class timed_thread(Thread): def __init__(self, time_start): Thread.__init__(self) self.time_start = time_start # Thread that just executes sleep() class sleep_thread(timed_thread): def run(self): sleep(15) print "st DONE:\t%f" % (time() - time_start) # Thread that increments a number for a while class spin_thread(timed_thread): def run(self): x = 1 while x < 120000000: x += 1 print "sp DONE:\t%f" % (time() - time_start) # Thread that calls math.factorial with a large number class factorial_thread(timed_thread): def run(self): factorial(50000) print "ft DONE:\t%f" % (time() - time_start) # the tests print print "sleep_thread test" time_start = time() st = sleep_thread(time_start) st.start() print "st.start:\t%f" % (time() - time_start) st.join(2) print "st.join:\t%f" % (time() - time_start) print "sleep alive:\t%r" % st.isAlive() print print "spin_thread test" time_start = time() sp = spin_thread(time_start) sp.start() print "sp.start:\t%f" % (time() - time_start) sp.join(2) print "sp.join:\t%f" % (time() - time_start) print "sp alive:\t%r" % sp.isAlive() print print "factorial_thread test" time_start = time() ft = factorial_thread(time_start) ft.start() print "ft.start:\t%f" % (time() - time_start) ft.join(2) print "ft.join:\t%f" % (time() - time_start) print "ft alive:\t%r" % ft.isAlive() And here is the output on Python 2.6.5 on CentOS x64: sleep_thread test st.start: 0.000675 st.join: 2.006963 sleep alive: True spin_thread test sp.start: 0.000595 sp.join: 2.010066 sp alive: True factorial_thread test ft DONE: 4.475453 ft.start: 4.475589 ft.join: 4.475615 ft alive: False st DONE: 10.994519 sp DONE: 12.054668 I've tried this on python 2.6.5 on CentOS x64, 2.7.2 on Windows x86 and the factorial thread does not return from start on either of them until the thread is done executing. I've also tried this with PyPy 1.8.0 on Windows x86, and there result is slightly different. The start does return immediately, but then the join doesn't time out! sleep_thread test st.start: 0.001000 st.join: 2.001000 sleep alive: True spin_thread test sp.start: 0.000000 sp DONE: 0.197000 sp.join: 0.236000 sp alive: False factorial_thread test ft.start: 0.032000 ft DONE: 9.011000 ft.join: 9.012000 ft alive: False st DONE: 12.763000

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  • Will lock() statement block all threads in the proccess/appdomain?

    - by MikeJ
    Maybe the question sounds silly, but I don't understand 'something about threads and locking and I would like to get a confirmation (here's why I ask). So, if I have 10 servers and 10 request in the same time come to each server, that's 100 request across the farm. Without locking, thats 100 request to the database. If I do something like this: private static readonly object myLockHolder = new object(); if (Cache[key] == null) { lock(myLockHolder) { if (Cache[key] == null) { Cache[key] = LengthyDatabaseCall(); } } } How many database requests will I do? 10? 100? Or as much as I have threads?

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  • In C# or .NET, is there a way to prevent other threads from invoking methods on a particular thread?

    - by YWE
    I have a Windows Forms application with a BackgroundWorker. In a method on the main form, a MessageBox is shown and the user must click the OK button to continue. Meanwhile, while the messagebox is being displayed, the BackgroundWorker finishes executing and calls the RunWorkerCompleted event. In the method I have assigned to that event, which runs on the UI thread, the Close method is called on the form. Even though the method that shows the message box is still running, the UI thread is not blocking other threads from invoking methods on it. So the Close method gets called on the form. What I want is for the UI thread to block other threads' invokes until the method with the message box has finished. Is there an easy way to do that?

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  • cpusets not working - threads aren't running in the cpuset I specified?

    - by lori
    I have used cpuset to shield some cpus for exclusive use by some realtime threads. Displaying the cpuset config with the test app RealtimeTest1 running and its tasks moved into the cpusets: $ cset set --list -r cset: Name CPUs-X MEMs-X Tasks Subs Path ------------ ---------- - ------- - ----- ---- ---------- root 0-23 y 0-1 y 279 2 / system 0,2,4,6,8,10 n 0 n 202 0 /system shield 1,3,5,7,9,11 n 1 n 0 2 /shield RealtimeTest1 1,3,5,7 n 1 n 0 4 /shield/RealtimeTest1 thread1 3 n 1 n 1 0 /shield/RealtimeTest1/thread1 thread2 5 n 1 n 1 0 /shield/RealtimeTest1/thread2 main 1 n 1 n 1 0 /shield/RealtimeTest1/main I can interrogate the cpuset filesystem to show that my tasks are supposedly pinned to the cpus I requested: /cpusets/shield/RealtimeTest1 $ for i in `find -name tasks`; do echo $i; cat $i; echo "------------"; done ./thread1/tasks 17651 ------------ ./main/tasks 17649 ------------ ./thread2/tasks 17654 ------------ Further, if I use sched_getaffinity, it reports what cpuset does - that thread1 is on cpu 3 and thread2 is on cpu 5. However, if I run top -p 17649 -H with f,j to bring up the last used cpu, it shows that thread 1 is running on thread 2's cpu, and main thread is running on a cpu in the system cpuset (Note that thread 17654 is running FIFO, hence thread 17651 is blocked) PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ P COMMAND 17654 root -2 0 54080 35m 7064 R 100 0.4 5:00.77 3 RealtimeTest 17649 root 20 0 54080 35m 7064 S 0 0.4 0:00.05 2 RealtimeTest 17651 root 20 0 54080 35m 7064 R 0 0.4 0:00.00 3 RealtimeTest Also, looking at /proc/17649/task to find the last_cpu each of its tasks ran on: /proc/17649/task $ for i in `ls -1`; do cat $i/stat | awk '{print $1 " is on " $(NF - 5)}'; done 17649 is on 2 17651 is on 3 17654 is on 3 So cpuset and sched_getaffinity reports one thing, but reality is another I would say that cpuset is not working? My machine configuration is: $ cat /etc/SuSE-release SUSE Linux Enterprise Server 11 (x86_64) VERSION = 11 PATCHLEVEL = 1 $ uname -a Linux foobar 2.6.32.12-0.7-default #1 SMP 2010-05-20 11:14:20 +0200 x86_64 x86_64 x86_64 GNU/Linux

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  • Inside the Concurrent Collections: ConcurrentBag

    - by Simon Cooper
    Unlike the other concurrent collections, ConcurrentBag does not really have a non-concurrent analogy. As stated in the MSDN documentation, ConcurrentBag is optimised for the situation where the same thread is both producing and consuming items from the collection. We'll see how this is the case as we take a closer look. Again, I recommend you have ConcurrentBag open in a decompiler for reference. Thread Statics ConcurrentBag makes heavy use of thread statics - static variables marked with ThreadStaticAttribute. This is a special attribute that instructs the CLR to scope any values assigned to or read from the variable to the executing thread, not globally within the AppDomain. This means that if two different threads assign two different values to the same thread static variable, one value will not overwrite the other, and each thread will see the value they assigned to the variable, separately to any other thread. This is a very useful function that allows for ConcurrentBag's concurrency properties. You can think of a thread static variable: [ThreadStatic] private static int m_Value; as doing the same as: private static Dictionary<Thread, int> m_Values; where the executing thread's identity is used to automatically set and retrieve the corresponding value in the dictionary. In .NET 4, this usage of ThreadStaticAttribute is encapsulated in the ThreadLocal class. Lists of lists ConcurrentBag, at its core, operates as a linked list of linked lists: Each outer list node is an instance of ThreadLocalList, and each inner list node is an instance of Node. Each outer ThreadLocalList is owned by a particular thread, accessible through the thread local m_locals variable: private ThreadLocal<ThreadLocalList<T>> m_locals It is important to note that, although the m_locals variable is thread-local, that only applies to accesses through that variable. The objects referenced by the thread (each instance of the ThreadLocalList object) are normal heap objects that are not specific to any thread. Thinking back to the Dictionary analogy above, if each value stored in the dictionary could be accessed by other means, then any thread could access the value belonging to other threads using that mechanism. Only reads and writes to the variable defined as thread-local are re-routed by the CLR according to the executing thread's identity. So, although m_locals is defined as thread-local, the m_headList, m_nextList and m_tailList variables aren't. This means that any thread can access all the thread local lists in the collection by doing a linear search through the outer linked list defined by these variables. Adding items So, onto the collection operations. First, adding items. This one's pretty simple. If the current thread doesn't already own an instance of ThreadLocalList, then one is created (or, if there are lists owned by threads that have stopped, it takes control of one of those). Then the item is added to the head of that thread's list. That's it. Don't worry, it'll get more complicated when we account for the other operations on the list! Taking & Peeking items This is where it gets tricky. If the current thread's list has items in it, then it peeks or removes the head item (not the tail item) from the local list and returns that. However, if the local list is empty, it has to go and steal another item from another list, belonging to a different thread. It iterates through all the thread local lists in the collection using the m_headList and m_nextList variables until it finds one that has items in it, and it steals one item from that list. Up to this point, the two threads had been operating completely independently. To steal an item from another thread's list, the stealing thread has to do it in such a way as to not step on the owning thread's toes. Recall how adding and removing items both operate on the head of the thread's linked list? That gives us an easy way out - a thread trying to steal items from another thread can pop in round the back of another thread's list using the m_tail variable, and steal an item from the back without the owning thread knowing anything about it. The owning thread can carry on completely independently, unaware that one of its items has been nicked. However, this only works when there are at least 3 items in the list, as that guarantees there will be at least one node between the owning thread performing operations on the list head and the thread stealing items from the tail - there's no chance of the two threads operating on the same node at the same time and causing a race condition. If there's less than three items in the list, then there does need to be some synchronization between the two threads. In this case, the lock on the ThreadLocalList object is used to mediate access to a thread's list when there's the possibility of contention. Thread synchronization In ConcurrentBag, this is done using several mechanisms: Operations performed by the owner thread only take out the lock when there are less than three items in the collection. With three or greater items, there won't be any conflict with a stealing thread operating on the tail of the list. If a lock isn't taken out, the owning thread sets the list's m_currentOp variable to a non-zero value for the duration of the operation. This indicates to all other threads that there is a non-locked operation currently occuring on that list. The stealing thread always takes out the lock, to prevent two threads trying to steal from the same list at the same time. After taking out the lock, the stealing thread spinwaits until m_currentOp has been set to zero before actually performing the steal. This ensures there won't be a conflict with the owning thread when the number of items in the list is on the 2-3 item borderline. If any add or remove operations are started in the meantime, and the list is below 3 items, those operations try to take out the list's lock and are blocked until the stealing thread has finished. This allows a thread to steal an item from another thread's list without corrupting it. What about synchronization in the collection as a whole? Collection synchronization Any thread that operates on the collection's global structure (accessing anything outside the thread local lists) has to take out the collection's global lock - m_globalListsLock. This single lock is sufficient when adding a new thread local list, as the items inside each thread's list are unaffected. However, what about operations (such as Count or ToArray) that need to access every item in the collection? In order to ensure a consistent view, all operations on the collection are stopped while the count or ToArray is performed. This is done by freezing the bag at the start, performing the global operation, and unfreezing at the end: The global lock is taken out, to prevent structural alterations to the collection. m_needSync is set to true. This notifies all the threads that they need to take out their list's lock irregardless of what operation they're doing. All the list locks are taken out in order. This blocks all locking operations on the lists. The freezing thread waits for all current lockless operations to finish by spinwaiting on each m_currentOp field. The global operation can then be performed while the bag is frozen, but no other operations can take place at the same time, as all other threads are blocked on a list's lock. Then, once the global operation has finished, the locks are released, m_needSync is unset, and normal concurrent operation resumes. Concurrent principles That's the essence of how ConcurrentBag operates. Each thread operates independently on its own local list, except when they have to steal items from another list. When stealing, only the stealing thread is forced to take out the lock; the owning thread only has to when there is the possibility of contention. And a global lock controls accesses to the structure of the collection outside the thread lists. Operations affecting the entire collection take out all locks in the collection to freeze the contents at a single point in time. So, what principles can we extract here? Threads operate independently Thread-static variables and ThreadLocal makes this easy. Threads operate entirely concurrently on their own structures; only when they need to grab data from another thread is there any thread contention. Minimised lock-taking Even when two threads need to operate on the same data structures (one thread stealing from another), they do so in such a way such that the probability of actually blocking on a lock is minimised; the owning thread always operates on the head of the list, and the stealing thread always operates on the tail. Management of lockless operations Any operations that don't take out a lock still have a 'hook' to force them to lock when necessary. This allows all operations on the collection to be stopped temporarily while a global snapshot is taken. Hopefully, such operations will be short-lived and infrequent. That's all the concurrent collections covered. I hope you've found it as informative and interesting as I have. Next, I'll be taking a closer look at ThreadLocal, which I came across while analyzing ConcurrentBag. As you'll see, the operation of this class deserves a much closer look.

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  • SQL SERVER – CXPACKET – Parallelism – Advanced Solution – Wait Type – Day 7 of 28

    - by pinaldave
    Earlier we discussed about the what is the common solution to solve the issue with CXPACKET wait time. Today I am going to talk about few of the other suggestions which can help to reduce the CXPACKET wait. If you are going to suggest that I should focus on MAXDOP and COST THRESHOLD – I totally agree. I have covered them in details in yesterday’s blog post. Today we are going to discuss few other way CXPACKET can be reduced. Potential Reasons: If data is heavily skewed, there are chances that query optimizer may estimate the correct amount of the data leading to assign fewer thread to query. This can easily lead to uneven workload on threads and may create CXPAKCET wait. While retrieving the data one of the thread face IO, Memory or CPU bottleneck and have to wait to get those resources to execute its tasks, may create CXPACKET wait as well. Data which is retrieved is on different speed IO Subsystem. (This is not common and hardly possible but there are chances). Higher fragmentations in some area of the table can lead less data per page. This may lead to CXPACKET wait. As I said the reasons here mentioned are not the major cause of the CXPACKET wait but any kind of scenario can create the probable wait time. Best Practices to Reduce CXPACKET wait: Refer earlier article regarding MAXDOP and Cost Threshold. De-fragmentation of Index can help as more data can be obtained per page. (Assuming close to 100 fill-factor) If data is on multiple files which are on multiple similar speed physical drive, the CXPACKET wait may reduce. Keep the statistics updated, as this will give better estimate to query optimizer when assigning threads and dividing the data among available threads. Updating statistics can significantly improve the strength of the query optimizer to render proper execution plan. This may overall affect the parallelism process in positive way. Bad Practice: In one of the recent consultancy project, when I was called in I noticed that one of the ‘experienced’ DBA noticed higher CXPACKET wait and to reduce them, he has increased the worker threads. The reality was increasing worker thread has lead to many other issues. With more number of the threads, more amount of memory was used leading memory pressure. As there were more threads CPU scheduler faced higher ‘Context Switching’ leading further degrading performance. When I explained all these to ‘experienced’ DBA he suggested that now we should reduce the number of threads. Not really! Lower number of the threads may create heavy stalling for parallel queries. I suggest NOT to touch the setting of number of the threads when dealing with CXPACKET wait. Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and I no way claim it to be accurate. I suggest reading book on-line for further clarification. All the discussion of Wait Stats over here is generic and it varies by system to system. You are recommended to test this on development server before implementing to production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: DMV, Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Safe to update separate regions of a BufferedImage in separate threads?

    - by finnw
    I have a collection of BufferedImage instances, one main image and some subimages created by calling getSubImage on the main image. The subimages do not overlap. I am also making modifications to the subimage and I want to split this into multiple threads, one per subimage. From my understanding of how BufferedImage, Raster and DataBuffer work, this should be safe because: Each instance of BufferedImage (and its respective WritableRaster) is accessed from only one thread. The shared ColorModel is immutable The DataBuffer has no fields that can be modified (the only thing that can change is elements of the backing array.) Modifying disjoint segments of an array in separate threads is safe. However I cannot find anything in the documentation that says that it is definitely safe to do this. Can I assume it is safe? I know that it is possible to work on copies of the child Rasters but I would prefer to avoid this because of memory constraints. Otherwise, is it possible to make the operation thread-safe without copying regions of the parent image?

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  • Why is my multithreaded Java program not maxing out all my cores on my machine?

    - by James B
    Hi, I have a program that starts up and creates an in-memory data model and then creates a (command-line-specified) number of threads to run several string checking algorithms against an input set and that data model. The work is divided amongst the threads along the input set of strings, and then each thread iterates the same in-memory data model instance (which is never updated again, so there are no synchronization issues). I'm running this on a Windows 2003 64-bit server with 2 quadcore processors, and from looking at Windows task Manager they aren't being maxed-out, (nor are they looking like they are being particularly taxed) when I run with 10 threads. Is this normal behaviour? It appears that 7 threads all complete a similar amount of work in a similar amount of time, so would you recommend running with 7 threads instead? Should I run it with more threads?...Although I assume this could be detrimental as the JVM will do more context switching between the threads. Alternatively, should I run it with fewer threads? Alternatively, what would be the best tool I could use to measure this?...Would a profiling tool help me out here - indeed, is one of the several profilers better at detecting bottlenecks (assuming I have one here) than the rest? Note, the server is also running SQL Server 2005 (this may or may not be relevant), but nothing much is happening on that database when I am running my program. Note also, the threads are only doing string matching, they aren't doing any I/O or database work or anything else they may need to wait on. Thanks in advance, -James

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