Abstract
The Message Passing Interface (MPI) is the prevalent programming model used on today's supercomputers. Therefore, MPI library developers are looking for the best possible performance (shortest run-time) of individual MPI functions across many different supercomputer architectures. Several MPI benchmark suites have been developed to assess the performance of MPI implementations. Unfortunately, the outcome of these benchmarks is often neither reproducible nor statistically sound. To overcome these issues, we show which experimental factors have an impact on the run-time of blocking collective MPI operations and how to control them. We address the problem of process and clock synchronization in MPI benchmarks. Finally, we present a new experimental method that allows us to obtain reproducible and statistically sound MPI measurements.
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