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Assessment of Applying the PMaC Prediction Framework to NERSC-5 SSP Benchmarks

Abstract

NERSC procurement depends on application benchmarks, in particular the NERSC SSP. Machine vendors are asked to run SSP benchmarks at various scales to enable NERSC to assess system performance. However, it is often the case that the vendor cannot run the benchmarks at large concurrency as it is impractical to have that much hardware available. Additionally, there may be difficulties in porting the benchmarks to the hardware. The Performance Modeling and Characterization Lab (PMaC) at San Diego Supercomputing Center (SDSC) have developed a framework to predict the performance of codes on large parallel machines. The goal of this work was to apply the PMaC prediction framework to the NERSC-5 SSP benchmark applications and ultimately consider the accuracy of the predictions. Other tasks included identifying assumptions and simplifications in the process, determining the ease of use, and measuring the resources required to obtain predictions.

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