Intel(R) MKL 11.0 introduces new functionality allowing users to balance the need for reproducible results with performance. The webinar recording and presentation linked below discusses the mechanisms that cause variability in floating point results, the new controls to limit these, and the performance trade-offs involved.
conditional numerical reproducibility
Conditional Numerical Reproducibility (CNR) in Intel MKL 11.0
New functionality in Intel MKL 11.0 now allows you to balance performance with reproducible results by allowing greater flexibility in code path choice and by ensuring that algorithms are deterministic. To learn more about Conditional Numerical Reproducibility (CNR) see the following resources:
Conditional Numerical Reproducibility (CNR) in Intel MKL 11.0
This article serves as a central repository for information on the new reproducibility features of Intel MKL
Webinar: Getting Reproducible Results with Intel® MKL 11.0 beta
A technical talk on the Condition Numerical Reproducibility (CNR) feature in Intel® MKL 11.0
