Simulation of reaction diffusion processes over biologically relevant size and time scales using multi-GPU workstations

Michael J. Hallock, John E. Stone, Elijah Roberts, Corey Fry, Zaida Luthey-Schulten

Research output: Contribution to journalArticlepeer-review

Abstract

Simulation of in vivo cellular processes with the reaction-diffusion master equation (RDME) is a computationally expensive task. Our previous software enabled simulation of inhomogeneous biochemical systems for small bacteria over long time scales using the MPD-RDME method on a single GPU. Simulations of larger eukaryotic systems exceed the on-board memory capacity of individual GPUs, and long time simulations of modest-sized cells such as yeast are impractical on a single GPU. We present a new multi-GPU parallel implementation of the MPD-RDME method based on a spatial decomposition approach that supports dynamic load balancing for workstations containing GPUs of varying performance and memory capacity. We take advantage of high-performance features of CUDA for peer-to-peer GPU memory transfers and evaluate the performance of our algorithms on state-of-the-art GPU devices. We present parallel efficiency and performance results for simulations using multiple GPUs as system size, particle counts, and number of reactions grow. We also demonstrate multi-GPU performance in simulations of the Min protein system in E. coli. Moreover, our multi-GPU decomposition and load balancing approach can be generalized to other lattice-based problems.

Original languageEnglish (US)
Pages (from-to)86-99
Number of pages14
JournalParallel Computing
Volume40
Issue number5-6
DOIs
StatePublished - May 2014

Keywords

  • Biological cells
  • Distributed memory parallel computing
  • GPU Computing
  • Gillespie algorithm
  • Reaction-diffusion master equation
  • Stochastic simulation

ASJC Scopus subject areas

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

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