title: High-performance blob-based iterative three-dimensional reconstruction in electron tomography using multi-GPUs.
abstract: BACKGROUND
  Three-dimensional (3D) reconstruction in 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 in ET, but demand huge computational costs. Multiple graphic processing units (multi-GPUs) offer an affordable platform to meet these demands. However, a synchronous communication scheme between multi-GPUs leads to idle GPU time, and a weighted matrix involved in iterative methods cannot be loaded into GPUs especially for large images due to the limited available memory of GPUs.
  
  
  RESULTS
  In this paper we propose a multilevel parallel strategy combined with an asynchronous communication scheme and a blob-ELLR data structure to efficiently perform blob-based iterative reconstructions on multi-GPUs. The asynchronous communication scheme is used to minimize the idle GPU time so as to asynchronously overlap communications with computations. 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.
  
  
  CONCLUSIONS
  Experimental results indicate that the multilevel parallel scheme combined with the asynchronous communication scheme and the blob-ELLR data structure allows efficient implementations of 3D reconstruction in ET on multi-GPUs.
authors: Institute of Computing Technology and Key Lab of Intelligent Information Processing, Beijing, China.
authors: Xiaohua
authors: X
authors: Wan
authors: Fa
authors: F
authors: Zhang
authors: Qi
authors: Q
authors: Chu
authors: Zhiyong
authors: Z
authors: Liu
mesh_terms: D000465:Algorithms; D055032:Electron Microscope Tomography; D007091:Image Processing, Computer-Assisted / Q000379:methods*