Development and performance of a HemeLB GPU code for human-scale blood flow simulation

I. Zacharoudiou, J. W.S. McCullough, P. V. Coveney*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
1 Downloads (Pure)

Abstract

In recent years, it has become increasingly common for high performance computers (HPC) to possess some level of heterogeneous architecture - typically in the form of GPU accelerators. In some machines these are isolated within a dedicated partition, whilst in others they are integral to all compute nodes - often with multiple GPUs per node - and provide the majority of a machine's compute performance. In light of this trend, it is becoming essential that codes deployed on HPC are updated to execute on accelerator hardware. In this paper we introduce a GPU implementation of the 3D blood flow simulation code HemeLB that has been developed using CUDA C++. We demonstrate how taking advantage of NVIDIA GPU hardware can achieve significant performance improvements compared to the equivalent CPU only code on which it has been built whilst retaining the excellent strong scaling characteristics that have been repeatedly demonstrated by the CPU version. With HPC positioned on the brink of the exascale era, we use HemeLB as a motivation to provide a discussion on some of the challenges that many users will face when deploying their own applications on upcoming exascale machines.
Original languageEnglish
Article number108548
JournalComputer Physics Communications
Volume282
Early online date30 Sept 2022
DOIs
Publication statusPublished - Jan 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 The Authors

Keywords

  • Blood flow modelling
  • High performance computing
  • Lattice Boltzmann method

ASJC Scopus subject areas

  • Hardware and Architecture
  • General Physics and Astronomy

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