Software Resource Disaggregation for HPC with Serverless Computing
DescriptionThe aggregated HPC resources with rigid allocation systems and programming models struggle to adapt to diverse and changing workloads. Thus, HPC systems fail to efficiently use the large pools of unused memory and increase the utilization of idle computing resources. Prior work attempted to increase the throughput and efficiency of supercomputing systems through workload co-location and resource disaggregation. However, these methods fail to provide a solution that can be applied to existing systems without major hardware modifications and performance losses. In this presentation, we propose to use the new cloud paradigm of serverless computing to improve the utilization of supercomputers. We show that the FaaS programming model can satisfy the requirements of high-performance applications. We demonstrate a software resource disaggregation approach where the co-location of functions allows to utilize idle cores and accelerators while retaining near-native performance.
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TimeMonday, 14 November 20229:40am - 9:50am CST
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