I'm trying to use the ThreadPool class that is available here
Unfortunately, this class has been designed in such a way to create its threads at creation time and join them in the destructor. To make it more flexible and to be able create threads several times in it, I have added the following function to this class:
void join_all() {
condition.notify_all();
for (std::thread &worker : workers) {
worker.join(); // I get blocked here
}
}
However, with this change, when running the following main:
int main() {
ThreadPool pool(4);
for (int i = 0; i < 8; ++i) {
pool.enqueue([i]() {
std::cout << "HELLO " << i << std::endl;
});
}
pool.join_all(); // here I am blocked
return 0;
}
My main thread will be blocked inside join_all function while trying to join the first thread.
What's the proper way to write join_all() function which would allow me to keep using the pool without terminating it?
The ThreadPool class already joins the threads on its destructor. But if you want to have your own join_all() function (for any reason), you should set the stop variable as well:
void join_all()
{
{
std::unique_lock<std::mutex> lock(queue_mutex);
stop = true;
}
condition.notify_all();
for (std::thread &worker : workers) {
worker.join();
}
}
Warning: Now, you should be careful about double joining on your threads. So, what I propose is to check the threads before joining (e.g. in the destructor):
for (std::thread &worker : workers)
{
if (worker.joinable())
{
worker.join();
}
}
With these changes, the code works without any infinite loops.
I have a Thread Pool where each thread must be a waiting thread and keep listening to new tasks to process them asynchronously (the processing takes some long time). However, in the following code I am not able to get this behaviour. The problem is that when I create the thread pool, they execute successfully the first task given. The process() function reaches de return 0; while threads are computing tasks, but it never returns to main(). It stands in the v.wait(l, [&] {return !tasks.empty(); }); line, that is, it still waits for new tasks to be pushed into the tasks queue and that never happens. I've readed that it's something related to the std::future destructor: If I am not wrong, I think that when process() reaches the return, the std::future destructor is called and it waits till all the threads ends, but they never ends!
Here's the code:
static int callings = 0;
class ThreadPool
{
private:
std::queue<int> tasks;
std::mutex m;
std::vector<std::future<void>> finished;
std::condition_variable v;
public:
void push_task(int arg) {
std::unique_lock<std::mutex> l(m);
tasks.push(arg);
v.notify_one(); // wake a thread to work on the task
}
void read_tasks() {
while (true) {
std::unique_lock<std::mutex> l(m);
if (tasks.empty()) {
//waits till new task
v.wait(l, [&] {return !tasks.empty(); }); //after completing the first task, the program stays here forever
}
int task = tasks.front(); // read task
tasks.pop(); //delete task
//run the task
std::this_thread::sleep_for(std::chrono::milliseconds(5 * 1000)); //simulate computation
}//while true
}
void create_thread_pool(int m_threads_count) {
for (int t_i = 0; t_i < m_threads_count; t_i++) {
finished.push_back(std::async(std::launch::async,[this] { read_tasks(); }));
printf("Thread %d is doing work...\n", t_i);
}
}
}; //ThreadPool
int process(){
ThreadPool pool;
if(callings == 0)
{
pool.create_thread_pool(4);
}
//give some task to do...
pool.push_task(callings);
callings++;
return 0; //point reached but never returning to main
}
int main(){
while(true){
// do things...
process();
// do more things...
// this does not execute, how to solve this?
}
return 0;
}
How can I return to main() while the threads keep waiting for new tasks without blocking?
Thanks in advance
In Qt 4.7 Reference for QThreadPool, we find:
void QThreadPool::releaseThread()
Releases a thread previously reserved by a call to reserveThread().
Note: Calling this function without previously reserving a thread
temporarily increases maxThreadCount(). This is useful when a thread
goes to sleep waiting for more work, allowing other threads to
continue. Be sure to call reserveThread() when done waiting, so that
the thread pool can correctly maintain the activeThreadCount().
See also reserveThread().
void QThreadPool::reserveThread()
Reserves one thread, disregarding activeThreadCount() and
maxThreadCount().
Once you are done with the thread, call releaseThread() to allow it to
be reused.
Note: This function will always increase the number of active threads.
This means that by using this function, it is possible for
activeThreadCount() to return a value greater than maxThreadCount().
See also releaseThread().
I want to use releaseThread() to make it possible to use nested concurrent map, but in the following code, it hangs in waitForFinished():
#include <QApplication>
#include <QMainWindow>
#include <QtConcurrentMap>
#include <QtConcurrentRun>
#include <QFuture>
#include <QThreadPool>
#include <QtTest/QTest>
#include <QFutureSynchronizer>
struct Task2 { // only calculation
typedef void result_type;
void operator()(int count) {
int k = 0;
for (int i = 0; i < count * 10; ++i) {
for (int j = 0; j < count * 10; ++j) {
k++;
}
}
assert(k >= 0);
}
};
struct Task1 { // will launch some other concurrent map
typedef void result_type;
void operator()(int count) {
QVector<int> vec;
for (int i = 0; i < 5; ++i) {
vec.push_back(i+count);
}
Task2 task;
QFuture<void> f = QtConcurrent::map(vec.begin(), vec.end(), task);
{
// with out releaseThread before wait, it will hang directly
QThreadPool::globalInstance()->releaseThread();
f.waitForFinished(); // BUG: may hang there
QThreadPool::globalInstance()->reserveThread();
}
}
};
int main() {
QThreadPool* gtpool = QThreadPool::globalInstance();
gtpool->setExpiryTimeout(50);
int count = 0;
for (;;) {
QVector<int> vec;
for (int i = 0; i < 40 ; i++) {
vec.push_back(i);
}
// launch a task with nested map
Task1 task; // Task1 will have nested concurrent map
QFuture<void> f = QtConcurrent::map(vec.begin(), vec.end(),task);
f.waitForFinished(); // BUG: may hang there
count++;
// waiting most of thread in thread pool expire
while (QThreadPool::globalInstance()->activeThreadCount() > 0) {
QTest::qSleep(50);
}
// launch a task only calculation
Task2 task2;
QFuture<void> f2 = QtConcurrent::map(vec.begin(), vec.end(), task2);
f2.waitForFinished(); // BUG: may hang there
qDebug() << count;
}
return 0;
}
This code will not run forever; it will hang in after many loops (1~10000), with all threads waiting for condition variable.
My questions are:
Why does it hang?
Can I fix it and keep the nested concurrent map?
dev env:
Linux version 2.6.32-696.18.7.el6.x86_64; Qt4.7.4; GCC 3.4.5
Windows 7; Qt4.7.4; mingw 4.4.0
The program hangs because of the race condition in QThreadPool when you try to deal with expiryTimeout. Here is the analysis in detail :
The problem in QThreadPool - source
When starting a task, QThreadPool did something along the lines of:
QMutexLocker locker(&mutex);
taskQueue.append(task); // Place the task on the task queue
if (waitingThreads > 0) {
// there are already running idle thread. They are waiting on the 'runnableReady'
// QWaitCondition. Wake one up them up.
waitingThreads--;
runnableReady.wakeOne();
} else if (runningThreadCount < maxThreadCount) {
startNewThread(task);
}
And the the thread's main loop looks like this:
void QThreadPoolThread::run()
{
QMutexLocker locker(&manager->mutex);
while (true) {
/* ... */
if (manager->taskQueue.isEmpty()) {
// no pending task, wait for one.
bool expired = !manager->runnableReady.wait(locker.mutex(),
manager->expiryTimeout);
if (expired) {
manager->runningThreadCount--;
return;
} else {
continue;
}
}
QRunnable *r = manager->taskQueue.takeFirst();
// run the task
locker.unlock();
r->run();
locker.relock();
}
}
The idea is that the thread will wait for a given amount of second for
a task, but if no task was added in a given amount of time, the thread
expires and is terminated. The problem here is that we rely on the
return value of runnableReady. If there is a task that is scheduled at
exactly the same time as the thread expires, then the thread will see
false and will expire. But the main thread will not restart any other
thread. That might let the application hang as the task will never be
run.
The quick workaround is to use a long expiryTime (30000 by default) and remove the while loop that waits for the threads expired.
Here is the main function modified, the program runs smoothly in Windows 7, 4 threads used by default :
int main() {
QThreadPool* gtpool = QThreadPool::globalInstance();
//gtpool->setExpiryTimeout(50); <-- don't set the expiry Timeout, use the default one.
qDebug() << gtpool->maxThreadCount();
int count = 0;
for (;;) {
QVector<int> vec;
for (int i = 0; i < 40 ; i++) {
vec.push_back(i);
}
// launch a task with nested map
Task1 task; // Task1 will have nested concurrent map
QFuture<void> f = QtConcurrent::map(vec.begin(), vec.end(),task);
f.waitForFinished(); // BUG: may hang there
count++;
/*
// waiting most of thread in thread pool expire
while (QThreadPool::globalInstance()->activeThreadCount() > 0)
{
QTest::qSleep(50);
}
*/
// launch a task only calculation
Task2 task2;
QFuture<void> f2 = QtConcurrent::map(vec.begin(), vec.end(), task2);
f2.waitForFinished(); // BUG: may hang there
qDebug() << count ;
}
return 0;
}
#tungIt's answer is good enough, I found the qtbug and fix commit, just for reference:
https://bugreports.qt.io/browse/QTBUG-3786
https://github.com/qt/qtbase/commit/a9b6a78e54670a70b96c122b10ad7bd64d166514#diff-6d5794cef91df41c39b5e7cc6b71d041
Relevant questions:
About C++11:
C++11: std::thread pooled?
Will async(launch::async) in C++11 make thread pools obsolete for avoiding expensive thread creation?
About Boost:
C++ boost thread reusing threads
boost::thread and creating a pool of them!
How do I get a pool of threads to send tasks to, without creating and deleting them over and over again? This means persistent threads to resynchronize without joining.
I have code that looks like this:
namespace {
std::vector<std::thread> workers;
int total = 4;
int arr[4] = {0};
void each_thread_does(int i) {
arr[i] += 2;
}
}
int main(int argc, char *argv[]) {
for (int i = 0; i < 8; ++i) { // for 8 iterations,
for (int j = 0; j < 4; ++j) {
workers.push_back(std::thread(each_thread_does, j));
}
for (std::thread &t: workers) {
if (t.joinable()) {
t.join();
}
}
arr[4] = std::min_element(arr, arr+4);
}
return 0;
}
Instead of creating and joining threads each iteration, I'd prefer to send tasks to my worker threads each iteration and only create them once.
This is adapted from my answer to another very similar post.
Let's build a ThreadPool class:
class ThreadPool {
public:
void Start();
void QueueJob(const std::function<void()>& job);
void Stop();
void busy();
private:
void ThreadLoop();
bool should_terminate = false; // Tells threads to stop looking for jobs
std::mutex queue_mutex; // Prevents data races to the job queue
std::condition_variable mutex_condition; // Allows threads to wait on new jobs or termination
std::vector<std::thread> threads;
std::queue<std::function<void()>> jobs;
};
ThreadPool::Start
For an efficient threadpool implementation, once threads are created according to num_threads, it's better not to
create new ones or destroy old ones (by joining). There will be a performance penalty, and it might even make your
application go slower than the serial version. Thus, we keep a pool of threads that can be used at any time (if they
aren't already running a job).
Each thread should be running its own infinite loop, constantly waiting for new tasks to grab and run.
void ThreadPool::Start() {
const uint32_t num_threads = std::thread::hardware_concurrency(); // Max # of threads the system supports
threads.resize(num_threads);
for (uint32_t i = 0; i < num_threads; i++) {
threads.at(i) = std::thread(ThreadLoop);
}
}
ThreadPool::ThreadLoop
The infinite loop function. This is a while (true) loop waiting for the task queue to open up.
void ThreadPool::ThreadLoop() {
while (true) {
std::function<void()> job;
{
std::unique_lock<std::mutex> lock(queue_mutex);
mutex_condition.wait(lock, [this] {
return !jobs.empty() || should_terminate;
});
if (should_terminate) {
return;
}
job = jobs.front();
jobs.pop();
}
job();
}
}
ThreadPool::QueueJob
Add a new job to the pool; use a lock so that there isn't a data race.
void ThreadPool::QueueJob(const std::function<void()>& job) {
{
std::unique_lock<std::mutex> lock(queue_mutex);
jobs.push(job);
}
mutex_condition.notify_one();
}
To use it:
thread_pool->QueueJob([] { /* ... */ });
ThreadPool::busy
void ThreadPool::busy() {
bool poolbusy;
{
std::unique_lock<std::mutex> lock(queue_mutex);
poolbusy = jobs.empty();
}
return poolbusy;
}
The busy() function can be used in a while loop, such that the main thread can wait the threadpool to complete all the tasks before calling the threadpool destructor.
ThreadPool::Stop
Stop the pool.
void ThreadPool::Stop() {
{
std::unique_lock<std::mutex> lock(queue_mutex);
should_terminate = true;
}
mutex_condition.notify_all();
for (std::thread& active_thread : threads) {
active_thread.join();
}
threads.clear();
}
Once you integrate these ingredients, you have your own dynamic threading pool. These threads always run, waiting for
job to do.
I apologize if there are some syntax errors, I typed this code and and I have a bad memory. Sorry that I cannot provide
you the complete thread pool code; that would violate my job integrity.
Notes:
The anonymous code blocks are used so that when they are exited, the std::unique_lock variables created within them
go out of scope, unlocking the mutex.
ThreadPool::Stop will not terminate any currently running jobs, it just waits for them to finish via active_thread.join().
You can use C++ Thread Pool Library, https://github.com/vit-vit/ctpl.
Then the code your wrote can be replaced with the following
#include <ctpl.h> // or <ctpl_stl.h> if ou do not have Boost library
int main (int argc, char *argv[]) {
ctpl::thread_pool p(2 /* two threads in the pool */);
int arr[4] = {0};
std::vector<std::future<void>> results(4);
for (int i = 0; i < 8; ++i) { // for 8 iterations,
for (int j = 0; j < 4; ++j) {
results[j] = p.push([&arr, j](int){ arr[j] +=2; });
}
for (int j = 0; j < 4; ++j) {
results[j].get();
}
arr[4] = std::min_element(arr, arr + 4);
}
}
You will get the desired number of threads and will not create and delete them over and over again on the iterations.
A pool of threads means that all your threads are running, all the time – in other words, the thread function never returns. To give the threads something meaningful to do, you have to design a system of inter-thread communication, both for the purpose of telling the thread that there's something to do, as well as for communicating the actual work data.
Typically this will involve some kind of concurrent data structure, and each thread would presumably sleep on some kind of condition variable, which would be notified when there's work to do. Upon receiving the notification, one or several of the threads wake up, recover a task from the concurrent data structure, process it, and store the result in an analogous fashion.
The thread would then go on to check whether there's even more work to do, and if not go back to sleep.
The upshot is that you have to design all this yourself, since there isn't a natural notion of "work" that's universally applicable. It's quite a bit of work, and there are some subtle issues you have to get right. (You can program in Go if you like a system which takes care of thread management for you behind the scenes.)
A threadpool is at core a set of threads all bound to a function working as an event loop. These threads will endlessly wait for a task to be executed, or their own termination.
The threadpool job is to provide an interface to submit jobs, define (and perhaps modify) the policy of running these jobs (scheduling rules, thread instantiation, size of the pool), and monitor the status of the threads and related resources.
So for a versatile pool, one must start by defining what a task is, how it is launched, interrupted, what is the result (see the notion of promise and future for that question), what sort of events the threads will have to respond to, how they will handle them, how these events shall be discriminated from the ones handled by the tasks. This can become quite complicated as you can see, and impose restrictions on how the threads will work, as the solution becomes more and more involved.
The current tooling for handling events is fairly barebones(*): primitives like mutexes, condition variables, and a few abstractions on top of that (locks, barriers). But in some cases, these abstrations may turn out to be unfit (see this related question), and one must revert to using the primitives.
Other problems have to be managed too:
signal
i/o
hardware (processor affinity, heterogenous setup)
How would these play out in your setting?
This answer to a similar question points to an existing implementation meant for boost and the stl.
I offered a very crude implementation of a threadpool for another question, which doesn't address many problems outlined above. You might want to build up on it. You might also want to have a look of existing frameworks in other languages, to find inspiration.
(*) I don't see that as a problem, quite to the contrary. I think it's the very spirit of C++ inherited from C.
Follwoing [PhD EcE](https://stackoverflow.com/users/3818417/phd-ece) suggestion, I implemented the thread pool:
function_pool.h
#pragma once
#include <queue>
#include <functional>
#include <mutex>
#include <condition_variable>
#include <atomic>
#include <cassert>
class Function_pool
{
private:
std::queue<std::function<void()>> m_function_queue;
std::mutex m_lock;
std::condition_variable m_data_condition;
std::atomic<bool> m_accept_functions;
public:
Function_pool();
~Function_pool();
void push(std::function<void()> func);
void done();
void infinite_loop_func();
};
function_pool.cpp
#include "function_pool.h"
Function_pool::Function_pool() : m_function_queue(), m_lock(), m_data_condition(), m_accept_functions(true)
{
}
Function_pool::~Function_pool()
{
}
void Function_pool::push(std::function<void()> func)
{
std::unique_lock<std::mutex> lock(m_lock);
m_function_queue.push(func);
// when we send the notification immediately, the consumer will try to get the lock , so unlock asap
lock.unlock();
m_data_condition.notify_one();
}
void Function_pool::done()
{
std::unique_lock<std::mutex> lock(m_lock);
m_accept_functions = false;
lock.unlock();
// when we send the notification immediately, the consumer will try to get the lock , so unlock asap
m_data_condition.notify_all();
//notify all waiting threads.
}
void Function_pool::infinite_loop_func()
{
std::function<void()> func;
while (true)
{
{
std::unique_lock<std::mutex> lock(m_lock);
m_data_condition.wait(lock, [this]() {return !m_function_queue.empty() || !m_accept_functions; });
if (!m_accept_functions && m_function_queue.empty())
{
//lock will be release automatically.
//finish the thread loop and let it join in the main thread.
return;
}
func = m_function_queue.front();
m_function_queue.pop();
//release the lock
}
func();
}
}
main.cpp
#include "function_pool.h"
#include <string>
#include <iostream>
#include <mutex>
#include <functional>
#include <thread>
#include <vector>
Function_pool func_pool;
class quit_worker_exception : public std::exception {};
void example_function()
{
std::cout << "bla" << std::endl;
}
int main()
{
std::cout << "stating operation" << std::endl;
int num_threads = std::thread::hardware_concurrency();
std::cout << "number of threads = " << num_threads << std::endl;
std::vector<std::thread> thread_pool;
for (int i = 0; i < num_threads; i++)
{
thread_pool.push_back(std::thread(&Function_pool::infinite_loop_func, &func_pool));
}
//here we should send our functions
for (int i = 0; i < 50; i++)
{
func_pool.push(example_function);
}
func_pool.done();
for (unsigned int i = 0; i < thread_pool.size(); i++)
{
thread_pool.at(i).join();
}
}
You can use thread_pool from boost library:
void my_task(){...}
int main(){
int threadNumbers = thread::hardware_concurrency();
boost::asio::thread_pool pool(threadNumbers);
// Submit a function to the pool.
boost::asio::post(pool, my_task);
// Submit a lambda object to the pool.
boost::asio::post(pool, []() {
...
});
}
You also can use threadpool from open source community:
void first_task() {...}
void second_task() {...}
int main(){
int threadNumbers = thread::hardware_concurrency();
pool tp(threadNumbers);
// Add some tasks to the pool.
tp.schedule(&first_task);
tp.schedule(&second_task);
}
Something like this might help (taken from a working app).
#include <memory>
#include <boost/asio.hpp>
#include <boost/thread.hpp>
struct thread_pool {
typedef std::unique_ptr<boost::asio::io_service::work> asio_worker;
thread_pool(int threads) :service(), service_worker(new asio_worker::element_type(service)) {
for (int i = 0; i < threads; ++i) {
auto worker = [this] { return service.run(); };
grp.add_thread(new boost::thread(worker));
}
}
template<class F>
void enqueue(F f) {
service.post(f);
}
~thread_pool() {
service_worker.reset();
grp.join_all();
service.stop();
}
private:
boost::asio::io_service service;
asio_worker service_worker;
boost::thread_group grp;
};
You can use it like this:
thread_pool pool(2);
pool.enqueue([] {
std::cout << "Hello from Task 1\n";
});
pool.enqueue([] {
std::cout << "Hello from Task 2\n";
});
Keep in mind that reinventing an efficient asynchronous queuing mechanism is not trivial.
Boost::asio::io_service is a very efficient implementation, or actually is a collection of platform-specific wrappers (e.g. it wraps I/O completion ports on Windows).
Edit: This now requires C++17 and concepts. (As of 9/12/16, only g++ 6.0+ is sufficient.)
The template deduction is a lot more accurate because of it, though, so it's worth the effort of getting a newer compiler. I've not yet found a function that requires explicit template arguments.
It also now takes any appropriate callable object (and is still statically typesafe!!!).
It also now includes an optional green threading priority thread pool using the same API. This class is POSIX only, though. It uses the ucontext_t API for userspace task switching.
I created a simple library for this. An example of usage is given below. (I'm answering this because it was one of the things I found before I decided it was necessary to write it myself.)
bool is_prime(int n){
// Determine if n is prime.
}
int main(){
thread_pool pool(8); // 8 threads
list<future<bool>> results;
for(int n = 2;n < 10000;n++){
// Submit a job to the pool.
results.emplace_back(pool.async(is_prime, n));
}
int n = 2;
for(auto i = results.begin();i != results.end();i++, n++){
// i is an iterator pointing to a future representing the result of is_prime(n)
cout << n << " ";
bool prime = i->get(); // Wait for the task is_prime(n) to finish and get the result.
if(prime)
cout << "is prime";
else
cout << "is not prime";
cout << endl;
}
}
You can pass async any function with any (or void) return value and any (or no) arguments and it will return a corresponding std::future. To get the result (or just wait until a task has completed) you call get() on the future.
Here's the github: https://github.com/Tyler-Hardin/thread_pool.
looks like threadpool is very popular problem/exercise :-)
I recently wrote one in modern C++; it’s owned by me and publicly available here - https://github.com/yurir-dev/threadpool
It supports templated return values, core pinning, ordering of some tasks.
all implementation in two .h files.
So, the original question will be something like this:
#include "tp/threadpool.h"
int arr[5] = { 0 };
concurency::threadPool<void> tp;
tp.start(std::thread::hardware_concurrency());
std::vector<std::future<void>> futures;
for (int i = 0; i < 8; ++i) { // for 8 iterations,
for (int j = 0; j < 4; ++j) {
futures.push_back(tp.push([&arr, j]() {
arr[j] += 2;
}));
}
}
// wait until all pushed tasks are finished.
for (auto& f : futures)
f.get();
// or just tp.end(); // will kill all the threads
arr[4] = *std::min_element(arr, arr + 4);
I found the pending tasks' future.get() call hangs on caller side if the thread pool gets terminated and leaves some tasks inside task queue. How to set future exception inside thread pool with only the wrapper std::function?
template <class F, class... Args>
std::future<std::result_of_t<F(Args...)>> enqueue(F &&f, Args &&...args) {
auto task = std::make_shared<std::packaged_task<std::result_of_t<F(Args...)>()>>(
std::bind(std::forward<F>(f), std::forward<Args>(args)...));
std::future<return_type> res = task->get_future();
{
std::unique_lock<std::mutex> lock(_mutex);
_tasks.push([task]() -> void { (*task)(); });
}
return res;
}
class StdThreadPool {
std::vector<std::thread> _workers;
std::priority_queue<TASK> _tasks;
...
}
struct TASK {
//int _func_return_value;
std::function<void()> _func;
int priority;
...
}
The Stroika library has a threadpool implementation.
Stroika ThreadPool.h
ThreadPool p;
p.AddTask ([] () {doIt ();});
Stroika's thread library also supports cancelation (cooperative) - so that when the ThreadPool above goes out of scope - it cancels any running tasks (similar to c++20's jthread).
I've written my own version of thread safe queue. However, when I run this program, it hangs/deadlocks itself.
Wondering, why is this locks/hangs forever.
void concurrentqueue::addtoQueue(const int number)
{
locker currentlock(lock_for_queue);
numberlist.push(number);
pthread_cond_signal(&queue_availability_condition);
}
int concurrentqueue::getFromQueue()
{
int number = 0;
locker currentlock(lock_for_queue);
if ( empty() )
{
pthread_cond_wait(&queue_availability_condition,&lock_for_queue);
}
number = numberlist.front();
numberlist.pop();
return number;
}
bool concurrentqueue::empty()
{
return numberlist.empty();
}
I've written, the class locker as RAII.
class locker
{
public:
locker(pthread_mutex_t& lockee): target(lockee)
{
pthread_mutex_lock(&target);
}
~locker()
{
pthread_mutex_unlock(&target);
}
private:
pthread_mutex_t target;
};
My writer/reader thread code is very simple. Writer thread, adds to the queue and reader thread, reads from the queue.
void * writeintoqueue(void* myqueue)
{
void *t = 0;
concurrentqueue *localqueue = (concurrentqueue *) myqueue;
for ( int i = 0; i < 10 ; ++i)
{
localqueue->addtoQueue(i*10);
}
pthread_exit(t);
}
void * readfromqueue(void* myqueue)
{
void *t = 0;
concurrentqueue *localqueue = (concurrentqueue *) myqueue;
int number = 0;
for ( int i = 0 ; i < 10 ; ++i)
{
number = localqueue->getFromQueue();
std::cout << "The number from the queue is " << number << std::endl;
}
pthread_exit(t);
}
This is definitely not safe:
if ( empty() )
{
pthread_cond_wait(&queue_availability_condition,&lock_for_queue);
}
If another thread that was not previously waiting calls getFromQueue() after addtoQueue() has signalled the condition variable and exited but before the waiting thread has aquired the lock then this thread could exit and expect the queue to have values in it. You must recheck that the queue is not empty.
Change the if into a while:
while ( empty() )
{
pthread_cond_wait(&queue_availability_condition,&lock_for_queue);
}
Reformulating spong's comment as an answer: your locker class should NOT be copying the pthread_mutex_t by value. You should use a reference or a pointer instead, e.g.:
class locker
{
public:
locker(pthread_mutex_t& lockee): target(lockee)
{
pthread_mutex_lock(&target);
}
~locker()
{
pthread_mutex_unlock(&target);
}
private:
pthread_mutex_t& target; // <-- this is a reference
};
The reason for this is that all pthreads data types should be treated as opaque types -- you don't know what's in them and should not copy them. The library does things like looking at a particular memory address to determine if a lock is held, so if there are two copies of a variable that indicates if the lock is held, odd things could happen, such as multiple threads appearing to succeed in locking the same mutex.
I tested your code, and it also deadlocked for me. I then ran it through Valgrind, and although it did not deadlock in that case (due to different timings, or maybe Valgrind only simulates one thread at a time), Valgrind reported numerous errors. After fixing locker to use a reference instead, it ran without deadlocking and without generating any errors in Valgrind.
See also Debugging with pthreads.