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Utilizing IBM Spectrum LSF Simulator to Understand the Impacts of Adding AI Workloads to Capability Supercomputing

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Abstract

Machine Learning and Artificial Intelligence has been identified as an emerging priority science area within the Department of Energy. Large scale accelerator based supercomputers like Summit, while traditionally employed for modeling and simulation, provide architectures that are suitable for accelerating the ML/AI workloads at scale. With the release of Summit in 2018, there was an increase in the number of ML/AI based projects seeking time on the machine. It quickly became apparent that the allocations and job runtimes for this workload deviated from traditional large scale modeling and simulation. Accommodating this new workload requires understanding the impacts to traditional large scale modeling and simulation

Content

A paper titled: Utilizing IBM Spectrum LSF Simulator to Understand the Impacts of Adding AI Workloads to Capability Supercomputing from Oak Ridge which IBM contributed to: https://www.osti.gov/biblio/2205452

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Document Information

Modified date:
01 February 2024

UID

ibm17114137