A Case For Intra-rack Resource Disaggregation in HPC Article Swipe
George Michelogiannakis
,
Benjamin Klenk
,
Brandon Cook
,
Min Yee Teh
,
Madeleine Glick
,
Larry Dennison
,
Keren Bergman
,
John Shalf
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1145/3514245
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1145/3514245
The expected halt of traditional technology scaling is motivating increased heterogeneity in high-performance computing (HPC) systems with the emergence of numerous specialized accelerators. As heterogeneity increases, so does the risk of underutilizing expensive hardware resources if we preserve today’s rigid node configuration and reservation strategies. This has sparked interest in resource disaggregation to enable finer-grain allocation of hardware resources to applications. However, there is currently no data-driven study of what range of disaggregation is appropriate in HPC. To that end, we perform a detailed analysis of key metrics sampled in NERSC’s Cori, a production HPC system that executes a diverse open-science HPC workload. In addition, we profile a variety of deep-learning applications to represent an emerging workload. We show that for a rack (cabinet) configuration and applications similar to Cori, a central processing unit with intra-rack disaggregation has a 99.5% probability to find all resources it requires inside its rack. In addition, ideal intra-rack resource disaggregation in Cori could reduce memory and NIC resources by 5.36% to 69.01% and still satisfy the worst-case average rack utilization.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3514245
- https://dl.acm.org/doi/pdf/10.1145/3514245
- OA Status
- diamond
- Cited By
- 36
- References
- 60
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4210363011
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4210363011Canonical identifier for this work in OpenAlex
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https://doi.org/10.1145/3514245Digital Object Identifier
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A Case For Intra-rack Resource Disaggregation in HPCWork title
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articleOpenAlex work type
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enPrimary language
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2022Year of publication
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2022-02-02Full publication date if available
- Authors
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George Michelogiannakis, Benjamin Klenk, Brandon Cook, Min Yee Teh, Madeleine Glick, Larry Dennison, Keren Bergman, John ShalfList of authors in order
- Landing page
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https://doi.org/10.1145/3514245Publisher landing page
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https://dl.acm.org/doi/pdf/10.1145/3514245Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://dl.acm.org/doi/pdf/10.1145/3514245Direct OA link when available
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Rack, Computer science, Workload, Reservation, Supercomputer, Resource (disambiguation), Variety (cybernetics), Distributed computing, Operating system, Artificial intelligence, Computer network, Law, Political scienceTop concepts (fields/topics) attached by OpenAlex
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2025: 10, 2024: 12, 2023: 10, 2022: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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