FSCHOL: An OpenCL-based HPC Framework for Accelerating Sparse Cholesky Factorization on FPGAs

Erfan Bank Tavakoli, Michael Riera, Masudul Hassan Quraishi, Fengbo Ren

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

Abstract

The proposed FSCHOL framework consists of an FPGA kernel implementing a throughput-optimized hardware architecture for accelerating the supernodal multifrontal algorithm for sparse Cholesky factorization and a host program implementing a novel scheduling algorithm for finding the optimal execution order of supernodes computations for an elimination tree on the FPGA to eliminate the need for off-chip memory access for storing intermediate results. Moreover, the proposed scheduling algorithm minimizes on-chip memory requirements for buffering intermediate results by resolving the dependency of parent nodes in an elimination tree through temporal parallelism. Experiment results for factorizing a set of sparse matrices in various sizes from SuiteSparse Matrix Collection show that the proposed FSCHOL implemented on an Intel Stratix 10 GX FPGA development board achieves on average 5.5× and 9.7× higher performance and 10.3× and 24.7× lower energy consumption than implementations of CHOLMOD on an Intel Xeon E5-2637 CPU and an NVIDIA V100 GPU, respectively.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 IEEE 33rd International Symposium on Computer Architecture and High Performance Computing, SBAC-PAD 2021
PublisherIEEE Computer Society
Pages209-220
Number of pages12
ISBN (Electronic)9781665443012
DOIs
StatePublished - 2021
Externally publishedYes
Event33rd IEEE International Symposium on Computer Architecture and High Performance Computing, SBAC-PAD 2021 - Virtual, Online, Brazil
Duration: Oct 26 2021Oct 29 2021

Publication series

NameProceedings - Symposium on Computer Architecture and High Performance Computing
ISSN (Print)1550-6533

Conference

Conference33rd IEEE International Symposium on Computer Architecture and High Performance Computing, SBAC-PAD 2021
Country/TerritoryBrazil
CityVirtual, Online
Period10/26/2110/29/21

Keywords

  • Cholesky factorization
  • FPGA
  • high-performance computing
  • OpenCL
  • reconfigurable computing
  • sparse matrix decomposition

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software

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