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Predictable GPU Sharing in Component-Based Real-Time Systems (Artifact)

Authors Syed W. Ali , Zelin Tong, Joseph Goh , James H. Anderson

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DARTS.10.1.1.pdf
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Subject Classification

ACM Subject Classification
  • Computer systems organization → Real-time systems
Keywords
  • GPU locking protocols
  • real-time locking protocols
  • priority-inversion blocking
  • component-based systems

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Abstract

This paper presents a real-time locking protocol whose design was motivated by the goal of enabling safe GPU sharing in time-sliced component-based systems. This locking protocol enables a GPU to be shared concurrently across, and utilized within, isolated components with predictable execution times. It relies on a novel resizing technique where GPU work is dimensioned on-the-fly to run on partitions of an NVIDIA GPU. This technique can be applied to any component that internally utilizes global CPU scheduling. The proposed locking protocol enables increased GPU parallelism and reduces GPU capacity loss with analytically provable benefits.

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Syed W. Ali, Zelin Tong, Joseph Goh, and James H. Anderson. Predictable GPU Sharing in Component-Based Real-Time Systems (Artifact). In Special Issue of the 36th Euromicro Conference on Real-Time Systems (ECRTS 2024). Dagstuhl Artifacts Series (DARTS), Volume 10, Issue 1, pp. 1:1-1:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/DARTS.10.1.1

Author Details

Syed W. Ali
  • Department of Computer Science, University of North Carolina at Chapel Hill, NC, USA
Zelin Tong
  • Department of Computer Science, University of North Carolina at Chapel Hill, NC, USA
Joseph Goh
  • Department of Computer Science, University of North Carolina at Chapel Hill, NC, USA
James H. Anderson
  • Department of Computer Science, University of North Carolina at Chapel Hill, NC, USA

Funding

Supported by NSF grants CPS 2038960, CPS 2038855, CNS 2151829, and CPS 2333120.

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  MD5 Sum: 59602553fb34de203b253b31a96c9cf4 (Get MD5 Sum)

Related Article

  • Syed W. Ali, Zelin Tong, Joseph Goh, and James H. Anderson, "Predictable GPU Sharing in Component-Based Real-Time Systems", in 36th Euromicro Conference on Real-Time Systems (ECRTS 2024), LIPIcs, Vol. 298, pp. 15:1-15:22, 2024. https://doi.org/10.4230/LIPIcs.ECRTS.2024.15

References

  1. Joshua Bakita and James H. Anderson. Hardware compute partitioning on NVIDIA GPUs*. In 2023 IEEE 29th Real-Time and Embedded Technology and Applications Symposium (RTAS), pages 54-66, 2023. URL: https://doi.org/10.1109/RTAS58335.2023.00012.
  2. Bjorn B. Brandenburg and James H. Anderson. Optimality results for multiprocessor real-time locking. In 2010 31st IEEE Real-Time Systems Symposium, pages 49-60, 2010. URL: https://doi.org/10.1109/RTSS.2010.17.
  3. P. Emberson, R. Stafford, and R.I. Davis. Techniques for the synthesis of multiprocessor tasksets. WATERS'10, January 2010. Google Scholar
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