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bioRxiv · 10.1101/075887

GeRelion: GPU-enhanced parallel implementation of single particle cryo-EM image processing

Huayou Su·Wen Wen·Xiaoli Du·Xicheng Lu·Maofu Liao·Dongsheng Li
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Abstract

Single particle cryo-EM emerges as a powerful and versatile method to characterize the structure and function of macromolecules, revealing the structural details of critical molecular machinery inside the cells. RELION is a widely used EM image processing software, and most of the recently published single particle cryo-EM structures were generated by using RELION. Due to the massive computational loads and the growing demands for processing much larger cryo-EM data sets, there is a pressing need to speed up image processing. Here we present GeRelion (https://github.com/gpu-pdl{not}nudt/GeRelion), an efficient parallel implementation of RELION on GPU system. In the performance tests using two cryo-EM data sets, GeRelion on 4 or 8 GPU cards outperformed RELION on 256 CPU cores, demonstrating dramatically improved speed and superb scalability. By greatly accelerating single particle cryo-EM structural analysis, GeRelion will facilitate both high resolution structure determination and dissection of mixed conformations of dynamic molecular machines.

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Huayou Su, Wen Wen, Xiaoli Du, Xicheng Lu, Maofu Liao, Dongsheng Li. 2016-09-19. GeRelion: GPU-enhanced parallel implementation of single particle cryo-EM image processing. https://doi.org/10.1101/075887

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