Parallel backends API#

Detailed Description#

API below is provided to resolve problem of CPU resource over-subscription by multiple thread pools from different multi-threading frameworks. This is common problem for cases when OpenCV compiled threading framework is different from the Users Applications framework.

Applications can replace OpenCV parallel_for() backend with own implementation (to reuse Application’s thread pool).

Backend API usage examples#

Plugins support#

Runtime configuration options:

  • change backend priority: OPENCV_PARALLEL_PRIORITY_<backend>=9999

  • disable backend: OPENCV_PARALLEL_PRIORITY_<backend>=0

  • specify list of backends with high priority (>100000): OPENCV_PARALLEL_PRIORITY_LIST=TBB,OPENMP. Unknown backends are registered as new plugins.

Classes#

Name

Description

class cv::parallel::ParallelForAPI

View details

class cv::parallel::openmp::ParallelForBackend

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class cv::parallel::tbb::ParallelForBackend

View details

Function Documentation#

setParallelForBackend() [1/2]#

void cv::parallel::setParallelForBackend(
const std::shared_ptr< ParallelForAPI > & api,
bool propagateNumThreads = true )

#include <opencv2/core/parallel/parallel_backend.hpp>

Replace OpenCV parallel_for backend.

Application can replace OpenCV parallel_for() backend with own implementation.

Note

This call is not thread-safe. Consider calling this function from the main() before any other OpenCV processing functions (and without any other created threads).

setParallelForBackend() [2/2]#

bool cv::parallel::setParallelForBackend(
const std::string & backendName,
bool propagateNumThreads = true )

#include <opencv2/core/parallel/parallel_backend.hpp>

Change OpenCV parallel_for backend.

Note

This call is not thread-safe. Consider calling this function from the main() before any other OpenCV processing functions (and without any other created threads).