| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2018 Google Inc. All rights reserved. | |
| // http://ceres-solver.org/ | |
| // | |
| // Redistribution and use in source and binary forms, with or without | |
| // modification, are permitted provided that the following conditions are met: | |
| // | |
| // * Redistributions of source code must retain the above copyright notice, | |
| // this list of conditions and the following disclaimer. | |
| // * Redistributions in binary form must reproduce the above copyright notice, | |
| // this list of conditions and the following disclaimer in the documentation | |
| // and/or other materials provided with the distribution. | |
| // * Neither the name of Google Inc. nor the names of its contributors may be | |
| // used to endorse or promote products derived from this software without | |
| // specific prior written permission. | |
| // | |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE | |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR | |
| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF | |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS | |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN | |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) | |
| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | |
| // POSSIBILITY OF SUCH DAMAGE. | |
| // | |
| // Author: vitus@google.com (Michael Vitus) | |
| // This include must come before any #ifndef check on Ceres compile options. | |
| #include "ceres/internal/config.h" | |
| #ifdef CERES_USE_CXX_THREADS | |
| #include <cmath> | |
| #include <condition_variable> | |
| #include <memory> | |
| #include <mutex> | |
| #include "ceres/concurrent_queue.h" | |
| #include "ceres/parallel_for.h" | |
| #include "ceres/scoped_thread_token.h" | |
| #include "ceres/thread_token_provider.h" | |
| #include "glog/logging.h" | |
| namespace ceres::internal { | |
| namespace { | |
| // This class creates a thread safe barrier which will block until a | |
| // pre-specified number of threads call Finished. This allows us to block the | |
| // main thread until all the parallel threads are finished processing all the | |
| // work. | |
| class BlockUntilFinished { | |
| public: | |
| explicit BlockUntilFinished(int num_total) | |
| : num_finished_(0), num_total_(num_total) {} | |
| // Increment the number of jobs that have finished and signal the blocking | |
| // thread if all jobs have finished. | |
| void Finished() { | |
| std::lock_guard<std::mutex> lock(mutex_); | |
| ++num_finished_; | |
| CHECK_LE(num_finished_, num_total_); | |
| if (num_finished_ == num_total_) { | |
| condition_.notify_one(); | |
| } | |
| } | |
| // Block until all threads have signaled they are finished. | |
| void Block() { | |
| std::unique_lock<std::mutex> lock(mutex_); | |
| condition_.wait(lock, [&]() { return num_finished_ == num_total_; }); | |
| } | |
| private: | |
| std::mutex mutex_; | |
| std::condition_variable condition_; | |
| // The current number of jobs finished. | |
| int num_finished_; | |
| // The total number of jobs. | |
| int num_total_; | |
| }; | |
| // Shared state between the parallel tasks. Each thread will use this | |
| // information to get the next block of work to be performed. | |
| struct SharedState { | |
| SharedState(int start, int end, int num_work_items) | |
| : start(start), | |
| end(end), | |
| num_work_items(num_work_items), | |
| i(0), | |
| thread_token_provider(num_work_items), | |
| block_until_finished(num_work_items) {} | |
| // The start and end index of the for loop. | |
| const int start; | |
| const int end; | |
| // The number of blocks that need to be processed. | |
| const int num_work_items; | |
| // The next block of work to be assigned to a worker. The parallel for loop | |
| // range is split into num_work_items blocks of work, i.e. a single block of | |
| // work is: | |
| // for (int j = start + i; j < end; j += num_work_items) { ... }. | |
| int i; | |
| std::mutex mutex_i; | |
| // Provides a unique thread ID among all active threads working on the same | |
| // group of tasks. Thread-safe. | |
| ThreadTokenProvider thread_token_provider; | |
| // Used to signal when all the work has been completed. Thread safe. | |
| BlockUntilFinished block_until_finished; | |
| }; | |
| } // namespace | |
| int MaxNumThreadsAvailable() { return ThreadPool::MaxNumThreadsAvailable(); } | |
| // See ParallelFor (below) for more details. | |
| void ParallelFor(ContextImpl* context, | |
| int start, | |
| int end, | |
| int num_threads, | |
| const std::function<void(int)>& function) { | |
| CHECK_GT(num_threads, 0); | |
| CHECK(context != nullptr); | |
| if (end <= start) { | |
| return; | |
| } | |
| // Fast path for when it is single threaded. | |
| if (num_threads == 1) { | |
| for (int i = start; i < end; ++i) { | |
| function(i); | |
| } | |
| return; | |
| } | |
| ParallelFor( | |
| context, start, end, num_threads, [&function](int /*thread_id*/, int i) { | |
| function(i); | |
| }); | |
| } | |
| // This implementation uses a fixed size max worker pool with a shared task | |
| // queue. The problem of executing the function for the interval of [start, end) | |
| // is broken up into at most num_threads blocks and added to the thread pool. To | |
| // avoid deadlocks, the calling thread is allowed to steal work from the worker | |
| // pool. This is implemented via a shared state between the tasks. In order for | |
| // the calling thread or thread pool to get a block of work, it will query the | |
| // shared state for the next block of work to be done. If there is nothing left, | |
| // it will return. We will exit the ParallelFor call when all of the work has | |
| // been done, not when all of the tasks have been popped off the task queue. | |
| // | |
| // A unique thread ID among all active tasks will be acquired once for each | |
| // block of work. This avoids the significant performance penalty for acquiring | |
| // it on every iteration of the for loop. The thread ID is guaranteed to be in | |
| // [0, num_threads). | |
| // | |
| // A performance analysis has shown this implementation is on par with OpenMP | |
| // and TBB. | |
| void ParallelFor(ContextImpl* context, | |
| int start, | |
| int end, | |
| int num_threads, | |
| const std::function<void(int thread_id, int i)>& function) { | |
| CHECK_GT(num_threads, 0); | |
| CHECK(context != nullptr); | |
| if (end <= start) { | |
| return; | |
| } | |
| // Fast path for when it is single threaded. | |
| if (num_threads == 1) { | |
| // Even though we only have one thread, use the thread token provider to | |
| // guarantee the exact same behavior when running with multiple threads. | |
| ThreadTokenProvider thread_token_provider(num_threads); | |
| const ScopedThreadToken scoped_thread_token(&thread_token_provider); | |
| const int thread_id = scoped_thread_token.token(); | |
| for (int i = start; i < end; ++i) { | |
| function(thread_id, i); | |
| } | |
| return; | |
| } | |
| // We use a std::shared_ptr because the main thread can finish all | |
| // the work before the tasks have been popped off the queue. So the | |
| // shared state needs to exist for the duration of all the tasks. | |
| const int num_work_items = std::min((end - start), num_threads); | |
| std::shared_ptr<SharedState> shared_state( | |
| new SharedState(start, end, num_work_items)); | |
| // A function which tries to perform a chunk of work. This returns false if | |
| // there is no work to be done. | |
| auto task_function = [shared_state, &function]() { | |
| int i = 0; | |
| { | |
| // Get the next available chunk of work to be performed. If there is no | |
| // work, return false. | |
| std::lock_guard<std::mutex> lock(shared_state->mutex_i); | |
| if (shared_state->i >= shared_state->num_work_items) { | |
| return false; | |
| } | |
| i = shared_state->i; | |
| ++shared_state->i; | |
| } | |
| const ScopedThreadToken scoped_thread_token( | |
| &shared_state->thread_token_provider); | |
| const int thread_id = scoped_thread_token.token(); | |
| // Perform each task. | |
| for (int j = shared_state->start + i; j < shared_state->end; | |
| j += shared_state->num_work_items) { | |
| function(thread_id, j); | |
| } | |
| shared_state->block_until_finished.Finished(); | |
| return true; | |
| }; | |
| // Add all the tasks to the thread pool. | |
| for (int i = 0; i < num_work_items; ++i) { | |
| // Note we are taking the task_function as value so the shared_state | |
| // shared pointer is copied and the ref count is increased. This is to | |
| // prevent it from being deleted when the main thread finishes all the | |
| // work and exits before the threads finish. | |
| context->thread_pool.AddTask([task_function]() { task_function(); }); | |
| } | |
| // Try to do any available work on the main thread. This may steal work from | |
| // the thread pool, but when there is no work left the thread pool tasks | |
| // will be no-ops. | |
| while (task_function()) { | |
| } | |
| // Wait until all tasks have finished. | |
| shared_state->block_until_finished.Block(); | |
| } | |
| } // namespace ceres::internal | |
| #endif // CERES_USE_CXX_THREADS |