The parallelization of SPIDER on distributed-memory computers using MPI

GPU-enabled FREALIGN: accelerating single particle 3D reconstruction and refinement in Fourier space on graphics processors

Among all the factors that determine the resolution of a 3D reconstruction by single particle electron cryo-microscopy (cryoEM), the number of particle images used in the dataset plays a major role. More images generally yield better resolution, assuming the imaged protein complex is conformationally and compositionally homogeneous. To facilitate processing of very large datasets, we modified the computer program, FREALIGN, to execute the computationally most intensive procedures on Graphics Processing Units (GPUs). Using the modified program, the execution speed increased between 10 and 240-fold depending on the task performed by FREALIGN. Here we report the steps necessary to parallelize critical FREALIGN subroutines and evaluate its performance on computers with multiple GPUs.

Low cost, high performance GPU computing solution for atomic resolution cryoEM single-particle reconstruction

Recent advancements in cryo-electron microscopy (cryoEM) have made it technically possible to determine the three-dimensional (3D) structures of macromolecular complexes at atomic resolution. However, processing the large amount of data needed for atomic resolution reconstructions requires either accessing to very expensive computer clusters or waiting for weeks of continuous computation in a personal computer (PC). In this paper, we present a practical computational solution to this 3D reconstruction problem through the optimal utilization of the processing capabilities of both commodity graphics hardware (i.e., general purpose graphics processing unit (GPGPU)). Our solution, which is implemented in a new program, called eLite3D, has a number of advanced features of general interests. First, we construct interleaved schemes to prevent the data race condition intrinsic in merging of 2D data into a 3D volume. Second, we introduce a processing pipeline strategy to optimally balance I/O and computation operations, thus improving CPU and GPGPU parallelism. The speedup of eLite3D is up to 100 times over other commonly used 3D reconstruction programs with the same accuracy, thus allowing completion of atomic resolution 3D reconstructions of large complexes in a PC in 1-2h other than days or weeks. Our result provides a practical solution to atomic resolution cryoEM (asymmetric or symmetric) reconstruction and offers useful guidelines for developing GPGPU applications in general.

A framework to refine particle clusters produced by EMAN

MOTIVATION

EMAN is one of the most popular software packages for single particle reconstruction. But the particle clusters produced during its model refining stage are of low qualities. We attempt to refine the particle clusters by more accurately determining orientations of particles, and thereby achieving higher resolutions of consequent 3D structures.

RESULTS

A particle reclustering framework (PRF) is introduced, which consists of three components. Each of them is responsible for one of the basic tasks of PRF: normalization, threshold determination and reclustering. Our implementation is also described and proved to meet the constraints proposed by PRF. Experiments revealed that our implementation improved resolutions of consequent structures for most cases, but only a little extra execution time was incurred. Therefore, it is practical to incorporate PRF in EMAN to improve qualities of generated 3D structures.

AVAILABILITY AND IMPLEMENTATION

Implementation of our algorithm is available upon request from the authors.

Software tools for molecular microscopy

In our role as the editors of a special edition of the Journal of Structural Biology published in 1996 and devoted to the development of software tools, we offer our view of past developments and future prospects in this area. The astonishing progress in computer hardware over the past decade has fueled a significant increase in computational power available for the solution of macromolecular structures. At the same time the relatively slow growth and development of the accompanying software reflects the difficulties of developing large, complex and very specialized analytical methods.