Getting Started with Conditional Numerical Reproducibility

Developer Guide

Contents

Getting Started with Conditional Numerical Reproducibility

Intel® oneAPI Math Kernel Library
 offers functions and environment variables to help you get reproducible results. You can configure
Intel® oneAPI Math Kernel Library
 using functions or environment variables, but the functions provide more flexibility.
The following specific examples introduce you to the conditional numerical reproducibility.
While these examples recommend aligning input and output data, you can supply unaligned data to
Intel® oneAPI Math Kernel Library
 functions running in the CNR mode, but refer toReproducibility Conditions for details related to data alignment.

Intel CPUs supporting Intel AVX2

To ensure
Intel® oneAPI Math Kernel Library
 calls return the same results on every Intel CPU supporting Intel AVX2 instructions:
  1. Make sure that your application uses a fixed number of threads
  2. (Recommended) Properly align input and output arrays in
    Intel® oneAPI Math Kernel Library
     function calls
  3. Do either of the following:
    • Call
      mkl_cbwr_set(MKL_CBWR_AVX2)
    • Set the environment variable:
      export MKL_CBWR = AVX2
On non-Intel CPUs and on Intel CPUs that do not support Intel AVX2, this environment setting may cause results to differ because the
AUTO
 branch is used instead, while the above function call returns an error and does not enable the CNR mode.

Intel CPUs supporting Intel SSE2

To ensure
Intel® oneAPI Math Kernel Library
 calls return the same results on every Intel CPU supporting Intel SSE2instructions:
  1. Make sure that your application uses a fixed number of threads
  2. (Recommended) Properly align input and output arrays in
    Intel® oneAPI Math Kernel Library
     function calls
  3. Do either of the following:
    • Call
      mkl_cbwr_set(MKL_CBWR_SSE2)
    • Set the environment variable:
      export MKL_CBWR = SSE2
On non-Intel CPUs, this environment setting may cause results to differ because the
AUTO
 branch is used instead, while the above function call returns an error and does not enable the CNR mode.

Intel or Intel compatible CPUs supporting Intel SSE2

On non-Intel CPUs, only the
MKL_CBWR_AUTO
 and
MKL_CBWR_COMPATIBLE
 options are supported for function calls and only
AUTO
 and
COMPATIBLE
 options for environment settings.
To ensure
Intel® oneAPI Math Kernel Library
 calls return the same results on all Intel or Intel compatible CPUs supporting Intel SSE2 instructions:
  1. Make sure that your application uses a fixed number of threads
  2. (Recommended) Properly align input and output arrays in
    Intel® oneAPI Math Kernel Library
     function calls
  3. Do either of the following:
    • Call
      mkl_cbwr_set(MKL_CBWR_COMPATIBLE)
    • Set the environment variable:
      export MKL_CBWR = COMPATIBLE
The special
MKL_CBWR_COMPATIBLE/COMPATIBLE
option is provided because Intel and Intel compatible CPUs have a few instructions, such as approximation instructions rcpps/rsqrtps, that may return different results. This option ensures that
Intel® oneAPI Math Kernel Library
 does not use these instructions and forces a single Intel SSE2 only code path to be executed.

Next steps

for details of specifying the branch using environment variables.
See the following sections in the
Intel® oneAPI Math Kernel Library
 Developer Reference
:
Support Functions for Conditional Numerical Reproducibility
for how to configure the CNR mode of
Intel® oneAPI Math Kernel Library
 using functions.
Intel® oneAPI Math Kernel Library
 PARDISO - Parallel Direct Sparse Solver Interface
for how to configure the CNR mode for PARDISO.
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.