High-performance Blob-based iterative reconstruction of electron tomography on multi-GPUs

Authors:
Xiaohua Wan;Fa Zhang;Qi Chu;Zhiyong Liu
Affiliations:
Institute of Computing Technology, Beijing, China and Graduate University, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Beijing, China;Institute of Computing Technology, Beijing, China and Graduate University, Chinese Academy of Sciences, Beijing, China;Institute of Computing Technology, Beijing, China
Venue:
ISBRA'11 Proceedings of the 7th international conference on Bioinformatics research and applications
Year:
2011

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Abstract

Three-dimensional (3D) reconstruction of electron tomography (ET) has emerged as a leading technique to elucidate the molecular structures of complex biological specimens. Blob-based iterative methods are advantageous reconstruction methods for 3D reconstruction of ET, but demand huge computational costs. Multiple Graphic processing units (multi-GPUs) offer an affordable platform to meet these demands, nevertheless, are not efficiently used owing to a synchronous communication scheme and the limited available memory of GPUs. We propose a multilevel parallel scheme combined with an asynchronous communication scheme and a blob-ELLR data structure. The asynchronous communication scheme is used to minimize the idle GPU time. The blob-ELLR data structure only needs nearly 1/16 of the storage space in comparison with ELLPACK-R (ELLR) data structure and yields significant acceleration. Experimental results indicate that the multilevel parallel scheme allows efficient implementations of 3D reconstruction of ET on multi-GPUs, without loss any resolution.