LLload: An Easy-to-Use HPC Utilization Tool

The increasing use and cost of high performance computing (HPC) requires new easy-to-use tools to enable HPC users and HPC systems engineers to transparently understand the utilization of resources. The MIT Lincoln Laboratory Supercomputing Center (LLSC) has developed a simple command, LLload, to monitor and characterize HPC workloads. LLload plays an important role in identifying opportunities for better utilization of compute resources. LLload can be used to monitor jobs both programmatically and interactively. LLload can characterize users' jobs using various LLload options to achieve better efficiency. This information can be used to inform the user to optimize HPC workloads and improve both CPU and GPU utilization. This includes improvements using judicious oversubscription of the computing resources. Preliminary results suggest significant improvement in GPU utilization and overall throughput performance with GPU overloading in some cases. By enabling users to observe and fix incorrect job submission and/or inappropriate execution setups, LLload can increase the resource usage and improve the overall throughput performance. LLload is a light-weight, easy-to-use tool for both HPC users and HPC systems engineers to monitor HPC workloads to improve system utilization and efficiency.

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Publication Details

Published
2024-09-23
DOI
https://doi.org/10.1109/hpec62836.2024.10938510
Citations
1
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.35
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article

LLload: An Easy-to-Use HPC Utilization Tool

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1 citations
Distributed and Parallel Computing Systems
0.35
article

LLload: An Easy-to-Use HPC Utilization Tool

Albert Reuther, Michael E. Houle, William Arcand, Bill Bergeron, Vijay Gadepally, Lauren Milechin, Michael T. Jones, Julie Mullen, Hayden Jananthan, Jeremy Kepner, David Bestor, Piotr Łuszczek, Matthew Hubbell, Chansup Byun, Guillermo Morales, Daniel Burrill, Andrew Prout, Antonio Rosa, Larry W. Anderson, Charles Yee, Peter Michaleas, Alexander Bonn
article en
1 citations

Abstract

The increasing use and cost of high performance computing (HPC) requires new easy-to-use tools to enable HPC users and HPC systems engineers to transparently understand the utilization of resources. The MIT Lincoln Laboratory Supercomputing Center (LLSC) has developed a simple command, LLload, to monitor and characterize HPC workloads. LLload plays an important role in identifying opportunities for better utilization of compute resources. LLload can be used to monitor jobs both programmatically and interactively. LLload can characterize users' jobs using various LLload options to achieve better efficiency. This information can be used to inform the user to optimize HPC workloads and improve both CPU and GPU utilization. This includes improvements using judicious oversubscription of the computing resources. Preliminary results suggest significant improvement in GPU utilization and overall throughput performance with GPU overloading in some cases. By enabling users to observe and fix incorrect job submission and/or inappropriate execution setups, LLload can increase the resource usage and improve the overall throughput performance. LLload is a light-weight, easy-to-use tool for both HPC users and HPC systems engineers to monitor HPC workloads to improve system utilization and efficiency.

Massachusetts Institute of Technology (US)
Openalex Percentile: Top 33%
Distributed and Parallel Computing Systems
0.35
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