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A Statistical Analysis of HPC Network Tuning
DescriptionDistributed scientific applications run on a complex stack of soft- ware and network technologies. Each layer has configuration options for tuning performance. These can range from protocol thresh- olds to algorithmic changes for collectives. Micro-benchmarks are a common methodology to evaluate the communication stack and are relatively easy to tune. However they aren’t representative of application behavior. Proxy applications, however, offer a simplified, but realistic, representation of the main computational and communicative methods in scientific programs. Since these proxy applications contain realistic message passing patterns, the correlation between micro-benchmarks and proxy application performance is not obvious. We present a study of statistically analyzing the impacts of tuning. Our results show how tuned micro-benchmark performance correlates with tuned proxy application performance.
Event Type
Workshop
TimeMonday, 13 November 20234:30pm - 4:50pm MST
Location605
Exascale
Message Passing
Programming Frameworks and System Software
W