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

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


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 languageEnglish (US)
Pages (from-to)102831
JournalParallel Computing
StatePublished - Sep 10 2021

Bibliographical 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.

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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