This Article Full Text (OnlineFirst PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Scopus Google Scholar Articles by Chung, J. Articles by Yang, C. Social Bookmarking                         What's this?

High Performance Three-Dimensional Image Reconstruction for Molecular Structure Determination

¹ Department of Mathematics and Computer Science, Emory University, Atlanta, GA, USA
² ILOG, An IBM Company, Incline Village, NV, USA
³ Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

^* To whom correspondence should be addressed. E-mail: jmchung{at}alum.emory.edu.

	Abstract

We describe an efficient parallel implementation of a reliable iterative reconstruction algorithm for estimating the three-dimensional (3D) density map of a macromolecular complex from a large number of two-dimensional (2D) cryo-electron microscopy (Cryo-EM) images. Our algorithm is based on a hybrid regularization approach first developed by Björck and O'Leary–Simmons. Our implementation uses a special data structure to represent the 3D density map to improve data locality in the reconstruction computation. Our parallelization strategy allows both 2D images and 3D data to be distributed on a 2D processor grid. We have used our implementation successfully on several datasets of different sizes, and we are able to achieve scalable parallel performance on a distributed memory cluster using over 15,000 CPUs for the largest dataset.

First published on June 16, 2009
International Journal of High Performance Computing Applications 2009, doi:10.1177/1094342009106293


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?