Developer Guide


Reproducibility Conditions

To get reproducible results from run to run, ensure that the number of threads is fixed and constant. Specifically:
  • If you are running your program with OpenMP* parallelization on different processors, explicitly specify the number of threads.
  • To ensure that your application has deterministic behavior with OpenMP* parallelization and does not adjust the number of threads dynamically at run time, set
    to FALSE. This is especially needed if you are running your program on different systems.
  • If you are running your program with the Intel® Threading Building Blocks parallelization, numerical reproducibility is not guaranteed.

Strict CNR Mode

In strict CNR mode,
oneAPI Math Kernel Library
provides bitwise reproducible results for a limited set of functions and code branches even when the number of threads changes. These routines and branches support strict CNR mode (64-bit libraries only):
When using other routines or CNR branches,
oneAPI Math Kernel Library
operates in standard (non-strict) CNR mode, subject to the restrictions described above. Enabling strict CNR mode can reduce performance.
  • As usual, you should align your data, even in CNR mode, to obtain the best possible performance. While CNR mode also fully supports unaligned input and output data, the use of it might reduce the performance of some
    oneAPI Math Kernel Library
    functions on earlier Intel processors. Refer to coding techniques that improve performance for more details.
  • Conditional Numerical Reproducibility does not ensure that bitwise-identical NaN values are generated when the input data contains NaN values.
  • If dynamic memory allocation fails on one run but succeeds on another run, you may fail to get reproducible results between these two runs.
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at
Notice revision #20201201

Product and Performance Information


Performance varies by use, configuration and other factors. Learn more at