4.7 Article

The PetscSF Scalable Communication Layer

期刊

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TPDS.2021.3084070

关键词

Libraries; Programming; Graphics processing units; Forestry; Electronics packaging; Arrays; Scalability; Communication; GPU; extreme-scale; MPI; PETSc

资金

  1. Exascale Computing Project of the U.S. Department of Energy Office of Science [17-SC-20-SC]
  2. Exascale Computing Project of the National Nuclear Security Administration [17-SC-20-SC]
  3. U.S. Department of Energy [DE-AC02-06CH11357]
  4. Office of Science [DE-SC0016140, DE-AC02-0000011838]
  5. DOE Office of Science User Facility [DE-AC05-00OR22725]
  6. U.S. Department of Energy (DOE) [DE-SC0016140] Funding Source: U.S. Department of Energy (DOE)

向作者/读者索取更多资源

PetscSF is the communication component of PETSc designed for exascale computers utilizing GPUs and other accelerators, providing a simple API for managing communication patterns in scientific computations. It supports various implementations based on MPI and NVSHMEM, essential for implementing large-scale applications.
PetscSF, the communication component of the Portable, Extensible Toolkit for Scientific Computation (PETSc), is designed to provide PETSc's communication infrastructure suitable for exascale computers that utilize GPUs and other accelerators. PetscSF provides a simple application programming interface (API) for managing common communication patterns in scientific computations by using a star-forest graph representation. PetscSF supports several implementations based on MPI and NVSHMEM, whose selection is based on the characteristics of the application or the target architecture. An efficient and portable model for network and intra-node communication is essential for implementing large-scale applications. The Message Passing Interface, which has been the de facto standard for distributed memory systems, has developed into a large complex API that does not yet provide high performance on the emerging heterogeneous CPU-GPU-based exascale systems. In this article, we discuss the design of PetscSF, how it can overcome some difficulties of working directly with MPI on GPUs, and we demonstrate its performance, scalability, and novel features.

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