Extensions to the SENSEI In situ Framework for Heterogeneous Architectures
Pages 868 - 874
Abstract
The proliferation of GPUs and accelerators in recent supercomputing systems, so called heterogeneous architectures, has led to increased complexity in execution environments and programming models as well as to deeper memory hierarchies on these systems. In this work, we discuss challenges that arise in in situ code coupling on these heterogeneous architectures. In particular, we present data and execution model extensions to the SENSEI in situ framework that are targeted at the effective use of systems with heterogeneous architectures. We then use these new data and execution model extensions to investigate several in situ placement and execution configurations and to analyze the impact these choices have on overall performance.
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Index Terms
- Extensions to the SENSEI In situ Framework for Heterogeneous Architectures
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Published In
November 2023
2180 pages
ISBN:9798400707858
DOI:10.1145/3624062
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
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Published: 12 November 2023
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SC-W 2023
SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
November 12 - 17, 2023
CO, Denver, USA
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