High-Performance Three-Dimensional Image Reconstruction for Molecular Structure Determination

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.