UC San Diego

This work presents an end-to-end methodology for quantifying the performance and power benefits of simultaneous multithreading (SMT) for HPC centers and applies this methodology to a production system and workload. Ultimately, SMT’s value system-wide depends on whether users effectively employ SMT at the application level. However, predicting SMT’s benefit for HPC applications is challenging; by doubling the number of threads, the application’s characteristics may change. This work proposes statistical modeling techniques to predict the speedup SMT confers to HPC applications. This approach, accurate to within 8%, uses only lightweight, transparent performance monitors collected during a single run of the application.