Developer Guide for Intel® oneAPI Math Kernel Library for MacOS*

Developer Guide

Contents

Avoiding Conflicts in the Execution Environment

Certain situations can cause conflicts in the execution environment that make the use of threads in
Intel® oneAPI Math Kernel Library
 problematic. This section briefly discusses why these problems exist and how to avoid them.
If your program is parallelized by means other than Intel® OpenMP* run-time library (RTL) and Intel® Threading Building Blocks (oneTBB) RTL, several calls to
Intel® oneAPI Math Kernel Library
 may operate in a multithreaded mode at the same time and result in slow performance due to overuse of machine resources.
The following table considers several cases where the conflicts may arise and provides recommendations depending on your threading model:
Threading model
Discussion
You parallelize the program
using the technology other than Intel OpenMP and oneTBB
(for example:
pthreads
 on
macOS*
).
If more than one thread calls
Intel® oneAPI Math Kernel Library
, and the function being called is threaded, it may be important that you turn off
Intel® oneAPI Math Kernel Library
 threading. Set the number of threads to one by any of the available means (seeTechniques to Set the Number of Threads).
You parallelize the program using OpenMP directives and/or pragmas and compile the program using a non-Intel compiler.
To avoid simultaneous activities of multiple threading RTLs, link the program against the
Intel® oneAPI Math Kernel Library
 threading library that matches the compiler you use
 (see on how to do this). If this is not possible, use
Intel® oneAPI Math Kernel Library
 in the sequential mode. To do this, you should link with the appropriate threading library:
lib
mkl_sequential.
a
 or
lib
mkl_sequential.
dylib
 (see Appendix C: Directory Structure in Detail).
You thread the program using oneTBB threading technology and compile the program using a non-Intel compiler.
To avoid simultaneous activities of multiple threading RTLs, link the program against the
Intel® oneAPI Math Kernel Library
 oneTBB threading library and oneTBB RTL if it matches the compiler you use. If this is not possible, use
Intel® oneAPI Math Kernel Library
 in the sequential mode. To do this, link with the appropriate threading library:
lib
mkl_sequential
.
a
 or
lib
mkl_sequential
.dylib
 (see Appendix C: Directory Structure in Detail).
You run multiple programs calling
Intel® oneAPI Math Kernel Library
 on a multiprocessor system, for example, a program parallelized using a message-passing interface (MPI).
The threading RTLs from different programs you run may place a large number of threads on the same processor on the system and therefore overuse the machine resources.
In this case, one of the solutions is to set the number of threads to one by any of the available means (see Techniques to Set the Number of Threads).
Using the
mkl_set_num_threads
 and
mkl_domain_set_num_threads
functions to control parallelism of
Intel® oneAPI Math Kernel Library
 from parallel user threads may result in a race condition that impacts the performance of the application because these functions operate on internal control variables that are global, that is, apply to all threads. For example, if parallel user threads call these functions to set different numbers of threads for the same function domain, the number of threads actually set is unpredictable. To avoid this kind of data races, use the
mkl_set_num_threads_local
 function (see the "Support Functions"
section
 in the
Intel® oneAPI Math Kernel Library
 Developer Reference
 for the function description).
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.
Notice revision #20201201

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.