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Accelerated high-performance computing through efficient multi-process GPU resource sharing

Published: 15 May 2012 Publication History

Abstract

The HPC field is witnessing a widespread adoption of GPUs as accelerators for traditional homogeneous HPC systems. One of the prevalent parallel programming models is the SPMD paradigm, which has been adapted for GPU-based parallel processing. Since each process executes the same program under SPMD, every process mapped to a CPU core also needs the GPU availability. Therefore SPMD demands a symmetric CPU/GPU distribution. However, since modern HPC systems feature a large number of CPU cores that outnumber the number of GPUs, computing resources are generally underutilized with SPMD. Our previous efforts have focused on GPU virtualization that enables efficient sharing of GPU among multiple CPU processes. Nevertheless, a formal method to evaluate and choose the appropriate GPU sharing approach is still lacking. In this paper, based on SPMD GPU kernel profiles, we propose different multi-process GPU sharing scenarios under virtualization. We introduce an analytical model that captures these sharing scenarios and provides a theoretical performance gain estimation. Benchmarks validate our analyses and achievable performance gains. While our analytical study provides a suitable theoretical foundation for GPU sharing, the experimental results demonstrate that GPU virtualization affords significant performance improvements over the non-virtualized solutions for all proposed sharing scenarios.

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  • (2023)Generative Agents: Interactive Simulacra of Human BehaviorProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606763(1-22)Online publication date: 29-Oct-2023
  • (2017)GPU Virtualization and Scheduling MethodsACM Computing Surveys10.1145/306828150:3(1-37)Online publication date: 29-Jun-2017
  • (2014)A complete and efficient CUDA-sharing solution for HPC clustersParallel Computing10.1016/j.parco.2014.09.01140:10(574-588)Online publication date: 1-Dec-2014
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Published In

cover image ACM Conferences
CF '12: Proceedings of the 9th conference on Computing Frontiers
May 2012
320 pages
ISBN:9781450312158
DOI:10.1145/2212908

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 May 2012

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Author Tags

  1. GPU
  2. HPC
  3. SPMD
  4. resource sharing
  5. virtualization

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CF'12
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CF'12: Computing Frontiers Conference
May 15 - 17, 2012
Cagliari, Italy

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Overall Acceptance Rate 273 of 785 submissions, 35%

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Cited By

View all
  • (2023)Generative Agents: Interactive Simulacra of Human BehaviorProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606763(1-22)Online publication date: 29-Oct-2023
  • (2017)GPU Virtualization and Scheduling MethodsACM Computing Surveys10.1145/306828150:3(1-37)Online publication date: 29-Jun-2017
  • (2014)A complete and efficient CUDA-sharing solution for HPC clustersParallel Computing10.1016/j.parco.2014.09.01140:10(574-588)Online publication date: 1-Dec-2014
  • (2013)Exploring Graphics Processing Unit (GPU) Resource Sharing Efficiency for High Performance ComputingComputers10.3390/computers20401762:4(176-214)Online publication date: 19-Nov-2013
  • (2013)Proactive routing based distributed energy consumption2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA)10.1109/SITA.2013.6560785(1-5)Online publication date: May-2013

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