Improving reaction kernel performance in lattice microbes: Particle-wise propensities and run-time generated code

Michael J. Hallock, Zaida Luthey-Schulten

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

Abstract

The reaction kernel for MPD-RDME, the GPU-accelerated reaction-diffusion master equation solver found in Lattice Microbes uses a large number of kinetic parameters to describe a biochemical network. Many of these parameters are required to compute the system's total reaction propensity, which is used to stochastically evaluate whether a reaction event takes place. In this paper, we examine two techniques for accelerating performance by modifying the total propensity calculation. The first technique is to use a particle-based approach to compute propensities from discrete particles and particle pairs. We find this technique results in a dramatic improvement in performance for a complex model, approximately 60 times faster. The second technique uses run-time generated source code to automatically create executable code tailored for the biological model being simulated. The removal of all memory reads for constant parameters increases performance for less complex models.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages428-434
Number of pages7
ISBN (Electronic)9781509021406
DOIs
StatePublished - Jul 18 2016
Event30th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2016 - Chicago, United States
Duration: May 23 2016May 27 2016

Publication series

NameProceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016

Other

Other30th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2016
CountryUnited States
CityChicago
Period5/23/165/27/16

ASJC Scopus subject areas

  • Computer Networks and Communications

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    Hallock, M. J., & Luthey-Schulten, Z. (2016). Improving reaction kernel performance in lattice microbes: Particle-wise propensities and run-time generated code. In Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016 (pp. 428-434). [7529899] (Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPDPSW.2016.118