High-Performance Blob-Based Iterative Reconstruction of Electron Tomography on Multi-GPUs

  • Xiaohua Wan
  • Fa Zhang
  • Qi Chu
  • Zhiyong Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6674)

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.

Keywords

electron tomography (ET) three-dimensional (3D) reconstruction iterative methods blob multi-GPUs 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xiaohua Wan
    • 1
    • 2
  • Fa Zhang
    • 1
  • Qi Chu
    • 1
    • 2
  • Zhiyong Liu
    • 1
  1. 1.Institute of Computing TechnologyChina
  2. 2.Graduate University, Chinese Academy of SciencesBeijingChina

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