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Parallel Optimization of Relion: Performance Comparison based on Cluster for CPU/GPU and KNL

Authors:

Fang ZhengAuthors Info & Claims

ICACS '18: Proceedings of the 2nd International Conference on Algorithms, Computing and Systems

Pages 48 - 52

https://doi.org/10.1145/3242840.3242871

Published: 27 July 2018 Publication History

Abstract

Relion is the 3D reconstruction program with the Bayes algorithm of electron cryo-microscope (cryo-EM) data. We analyzed the characteristics of the Relion program, and designed a parallelization scheme. We use the optimization methods commonly used in the code optimization for Relion programs, such as memory access optimization, multithread optimization, vectorization and conversing coarse grained parallel to fine-grained parallelism. Finally, the overall running time of the entire Relion program was reduced by 379s. At the same time, we tested the program on GPU and KNL platform and compared the results of the Relion program on the KNL cluster platform and the GPU cluster platform. The results show that the optimization effect of Relion on the GPU platform is better than KNL.

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Digital Library

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Scheres S H W. RELION: Implementation of a Bayesian approach to cryo-EM structure determination{J}. Journal of Structural Biology, 2012, 180(3):519--530.

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Kimanius D, Forsberg B O, Scheres S H, et al. Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2{J}. Elife, 2016, 5.

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Cited By

Qiao LYu HWang KSun RZhao WFu HYang G(2019)Large-scale Parallel Design for Cryo-EM Structure Determination on Heterogeneous Many-core Architectures2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM47256.2019.8983081(711-716)Online publication date: Nov-2019
https://doi.org/10.1109/BIBM47256.2019.8983081

Index Terms

Parallel Optimization of Relion: Performance Comparison based on Cluster for CPU/GPU and KNL
1. Theory of computation
  1. Design and analysis of algorithms
    1. Parallel algorithms
      1. Massively parallel algorithms

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cover image ACM Other conferences

ICACS '18: Proceedings of the 2nd International Conference on Algorithms, Computing and Systems

July 2018

245 pages

ISBN:9781450365093

DOI:10.1145/3242840

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 July 2018

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Natural Science Foundation of Hubei Province of China
Fundamental Research Funds for the Central Universities

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ICACS '18

ICACS '18: 2018 2nd International Conference on Algorithms, Computing and Systems

July 27 - 29, 2018

Beijing, China

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Cited By

Qiao LYu HWang KSun RZhao WFu HYang G(2019)Large-scale Parallel Design for Cryo-EM Structure Determination on Heterogeneous Many-core Architectures2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM47256.2019.8983081(711-716)Online publication date: Nov-2019
https://doi.org/10.1109/BIBM47256.2019.8983081

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