Improving Performance with Threading

Intel® Math Kernel Library (Intel® MKL) is extensively parallelized. See OpenMP* Threaded Functions and Problems and Functions Threaded with Intel® Threading Building Blocks for lists of threaded functions and problems that can be threaded.

Intel MKL is thread-safe, which means that all Intel MKL functions (except the LAPACK deprecated routine ?lacon) work correctly during simultaneous execution by multiple threads. In particular, any chunk of threaded Intel MKL code provides access for multiple threads to the same shared data, while permitting only one thread at any given time to access a shared piece of data. Therefore, you can call Intel MKL from multiple threads and not worry about the function instances interfering with each other.

If you are using OpenMP* threading technology, you can use the environment variable OMP_NUM_THREADS to specify the number of threads or the equivalent OpenMP run-time function calls. Intel MKL also offers variables that are independent of OpenMP, such as MKL_NUM_THREADS, and equivalent Intel MKL functions for thread management. The Intel MKL variables are always inspected first, then the OpenMP variables are examined, and if neither is used, the OpenMP software chooses the default number of threads.

By default, Intel MKL uses the number of OpenMP threads equal to the number of physical cores on the system.

If you are using the Intel TBB threading technology, the OpenMP threading controls, such as the OMP_NUM_THREADS environment variable or MKL_NUM_THREADS function, have no effect. Use the Intel TBB application programming interface to control the number of threads.

To achieve higher performance, set the number of threads to the number of processors or physical cores, as summarized in Techniques to Set the Number of Threads.