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Workload characterization is an integral part of performance analysis of highperformance computing (HPC) systems. An understanding of workload propertiessheds light on resource utilization and can be used to inform performanceoptimization both at the software and system configuration levels. It canprovide information on how computational science usage modalities are changingthat could potentially aid holistic capacity planning for the wider HPCecosystem. Here, we report on the results of a detailed workload analysis ofthe portfolio of supercomputers comprising the NSF Innovative HPC program inorder to characterize its past and current workload and look for trends tounderstand the nature of how the broad portfolio of computational scienceresearch is being supported and how it is changing over time. The workloadanalysis also sought to illustrate a wide variety of usage patterns andperformance requirements for jobs running on these systems. File systemperformance, memory utilization and the types of parallelism employed by users(MPI, threads, etc) were also studied for all systems for which job levelperformance data was available.

A Workload Analysis of NSF's Innovative HPC Resources Using XDMoD