CharminG: A Scalable GPU-resident Runtime System

Jaemin Choi, David F. Richards, Laxmikant V. Kale

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Host-driven execution of applications on modern GPU-accelerated systems suffer from frequent host-device synchronizations, data movement and limited flexibility in scheduling user tasks. We present CharminG, a runtime system designed to run entirely on the GPU without any interaction with the host. CharminG takes inspiration from the Charm++ parallel programming system and implements processor virtualization and message-driven execution on the GPU. We evaluate the composability and preliminary performance of CharminG with a proxy application that performs the Jacobi iterative method in a two-dimensional grid, using the Lassen supercomputer at Lawrence Livermore National Laboratory.

Original languageEnglish (US)
Title of host publicationHPDC 2021 - Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing
PublisherAssociation for Computing Machinery, Inc
Pages261-262
Number of pages2
ISBN (Electronic)9781450382175
DOIs
StatePublished - Jun 21 2021
Event30th International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2021 - Virtual, Online, Sweden
Duration: Jun 21 2021Jun 25 2021

Publication series

NameHPDC 2021 - Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing

Conference

Conference30th International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2021
Country/TerritorySweden
CityVirtual, Online
Period6/21/216/25/21

Keywords

  • cuda
  • gpu-resident runtime system
  • message-driven execution
  • nvshmem

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Computational Theory and Mathematics

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