Toward performance-portable PETSc for GPU-based exascale systems

Richard Tran Mills; Mark F. Adams; Satish Balay; Jed Brown; Alp Dener; Matthew Knepley; Scott E. Kruger; Hannah Morgan; Todd Munson; Karl Rupp; Barry F. Smith; Stefano Zampini; Hong Zhang; Junchao Zhang

doi:10.1016/j.parco.2021.102831

Toward performance-portable PETSc for GPU-based exascale systems

Richard Tran Mills, Mark F. Adams, Satish Balay, Jed Brown, Alp Dener, Matthew Knepley, Scott E. Kruger, Hannah Morgan, Todd Munson, Karl Rupp, Barry F. Smith, Stefano Zampini, Hong Zhang, Junchao Zhang

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Contribution to journal › Article › peer-review

31 Scopus citations

Abstract

The Portable Extensible Toolkit for Scientific computation (PETSc) library delivers scalable solvers for nonlinear time-dependent differential and algebraic equations and for numerical optimization. The PETSc design for performance portability addresses fundamental GPU accelerator challenges and stresses flexibility and extensibility by separating the programming model used by the application from that used by the library, and it enables application developers to use their preferred programming model, such as Kokkos, RAJA, SYCL, HIP, CUDA, or OpenCL, on upcoming exascale systems. A blueprint for using GPUs from PETSc-based codes is provided, and case studies emphasize the flexibility and high performance achieved on current GPU-based systems.

Original language	English (US)
Pages (from-to)	102831
Journal	Parallel Computing
Volume	108
DOIs	https://doi.org/10.1016/j.parco.2021.102831
State	Published - Sep 10 2021

ASJC Scopus subject areas

Artificial Intelligence
Hardware and Architecture
Theoretical Computer Science
Computer Graphics and Computer-Aided Design
Software
Computer Networks and Communications

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10.1016/j.parco.2021.102831

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title = "Toward performance-portable PETSc for GPU-based exascale systems",

abstract = "The Portable Extensible Toolkit for Scientific computation (PETSc) library delivers scalable solvers for nonlinear time-dependent differential and algebraic equations and for numerical optimization. The PETSc design for performance portability addresses fundamental GPU accelerator challenges and stresses flexibility and extensibility by separating the programming model used by the application from that used by the library, and it enables application developers to use their preferred programming model, such as Kokkos, RAJA, SYCL, HIP, CUDA, or OpenCL, on upcoming exascale systems. A blueprint for using GPUs from PETSc-based codes is provided, and case studies emphasize the flexibility and high performance achieved on current GPU-based systems.",

author = "Mills, {Richard Tran} and Adams, {Mark F.} and Satish Balay and Jed Brown and Alp Dener and Matthew Knepley and Kruger, {Scott E.} and Hannah Morgan and Todd Munson and Karl Rupp and Smith, {Barry F.} and Stefano Zampini and Hong Zhang and Junchao Zhang",

note = "KAUST Repository Item: Exported on 2021-10-11 Acknowledgements: This work was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two US Department of Energy organizations (Office of Science and the National Nuclear Security Administration), responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering, and early testbed platforms, in support of the nation's exascale computing imperative, and by the Austrian Science Fund (FWF) under grant P29119-N30. This research used resources of the Argonne and Oak Ridge Leadership Computing Facilities, DOE Office of Science User Facilities supported under Contracts DE-AC02-06CH11357 and DE-AC05-00OR22725, respectively.",

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AU - Adams, Mark F.

AU - Balay, Satish

AU - Brown, Jed

AU - Dener, Alp

AU - Knepley, Matthew

AU - Kruger, Scott E.

AU - Morgan, Hannah

AU - Munson, Todd

AU - Rupp, Karl

AU - Smith, Barry F.

AU - Zampini, Stefano

AU - Zhang, Hong

AU - Zhang, Junchao

N1 - KAUST Repository Item: Exported on 2021-10-11 Acknowledgements: This work was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two US Department of Energy organizations (Office of Science and the National Nuclear Security Administration), responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering, and early testbed platforms, in support of the nation's exascale computing imperative, and by the Austrian Science Fund (FWF) under grant P29119-N30. This research used resources of the Argonne and Oak Ridge Leadership Computing Facilities, DOE Office of Science User Facilities supported under Contracts DE-AC02-06CH11357 and DE-AC05-00OR22725, respectively.

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Toward performance-portable PETSc for GPU-based exascale systems

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