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[bos #42217][EDF 28921] Horseshoe with bodyfitting.
Fixed endless loop of creating threads and crash for an edge case when num of threads greater than num of hexaedrons to compute.
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@ -517,23 +517,66 @@ namespace Cartesian3D
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// Implement parallel computation of Hexa with c++ thread implementation
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template<typename Iterator, class Function>
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void parallel_for(const Iterator& first, const Iterator& last, Function&& f, const int nthreads = 1)
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void parallel_for(const Iterator& first, const Iterator& last, Function&& f, const unsigned int nthreads = 1)
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{
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const unsigned int group = ((last-first))/std::abs(nthreads);
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MESSAGE("Start parallel computation of Hexa with c++ threads...");
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assert(nthreads > 0);
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const unsigned int numTasksTotal = last - first;
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std::vector<std::thread> threads;
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threads.reserve(nthreads);
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Iterator it = first;
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for (; it < last-group; it += group) {
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// to create a thread
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// Pass iterators by value and the function by reference!
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auto lambda = [=,&f](){ std::for_each(it, std::min(it+group, last), f);};
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// stack the threads
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threads.push_back( std::thread( lambda ) );
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MESSAGE("Number of elements to compute: " << numTasksTotal << "; num of threads: " << nthreads);
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// Distribute tasks among threads
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if (numTasksTotal <= nthreads)
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{
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// A simple case - just one task executed in one thread.
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// TODO: check if it's faster to do it sequentially
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threads.reserve(numTasksTotal);
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for (; it < last; ++it)
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{
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threads.emplace_back(f, std::ref(*it));
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}
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std::for_each(it, last, f); // last steps while we wait for other threads
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std::for_each(threads.begin(), threads.end(), [](std::thread& x){x.join();});
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}
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else
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{
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// Calculate how to distribute elements among threads evenly
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const unsigned int numTasksInThread = numTasksTotal / nthreads;
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MESSAGE("Number of tasks in thread: " << numTasksInThread);
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// Store the numbers of tasks per thread
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std::vector<unsigned int> distTasksInThreads(nthreads, numTasksInThread);
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// Distribute a remainder among saved numbers
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const unsigned int remainder = numTasksTotal % nthreads;
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MESSAGE("Remainder of tasks " << remainder << " will be evenly distributed among threads");
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for (unsigned int i = 0; i < remainder; ++i)
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{
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++distTasksInThreads[i];
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}
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// Create threads for each number of tasks
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threads.reserve(nthreads);
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for (const auto i : distTasksInThreads)
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{
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Iterator curLast = it + i;
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// Pass iterators by value and the function by reference!
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auto lambda = [=,&f](){ std::for_each(it, curLast, f); };
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// Create a thread
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threads.emplace_back(lambda);
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// Advance iterator to the next step
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it = curLast;
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}
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}
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std::for_each(threads.begin(), threads.end(), [](std::thread& x){ x.join(); });
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MESSAGE("Parallel computation was finished successfully");
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}
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// --------------------------------------------------------------------------
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