Largescale Parallel Design for CryoEM Structure Determination on Heterogeneous Manycore Architectures CryoEM structure determination is the most important research area in structural biology. With the development of cryoelectron microscopy, the resolution has been enhanced significantly, which leads to the huge computation to reconstruct the biomolecule in recent years. In this paper, we present a largescale parallel design for CryoEM structure determination on heterogeneous manycore architectures. A novel task parallel strategy is proposed to reduce the redundant computation and improve the scalability on largescale systems. Further, We distribute the reconstruction model to each node and rearrange the data layout to achieve high parallel efficiency and reduce the memory footprint. The proposed comprehensive parallel design shows highly parallel efficiency and scalability on largescale heterogeneous architectures, which could significantly accelerate the whole period of CryoEM structure determination process.

A Weighted Voting Algorithm for Detecting Reliable Common Lines in Single Particle CryoEM The singleparticle reconstruction of cryoelectron microscopy is an important technique to recover the threedimensional structure of biological macromolecules from their twodimensional noisy projection images taken from unknown random directions. Angular reconstruction is a basic algorithm for reference free abinitio estimation of the initial threedimensional structure of molecules, in which the relative orientation of the particle is uniquely determined from the common lines among three projection images. However, it is difficult to detect reliable common lines due to the low signaltonoise ratio of the projection images. In this paper, a weighted voting algorithm is proposed to detect the reliable common lines, in which the iterative improvement technique is employed. The reliability of each common line is estimated by the consistency between the voted angle and projection angle computed using the common line during the iteration. Finally, the reliable common line pairs are retained, and the spurious ones are eliminated through the binary weight correction and iterative improvement. The proposed algorithm is successfully applied to the reconstruction of the Escherichia coli 50S ribosomal subunit. Experimental results show that the proposed algorithm can improve the estimation accuracy from noisy projection images.