Computer simulation of liquids
Computer simulation of liquids
General purpose molecular dynamics simulations fully implemented on graphics processing units
Journal of Computational Physics
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
Parallel verlet neighbor list algorithm for GPU-optimized MD simulations
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
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Molecular dynamics (MD) simulations provide a molecular-resolution view of biomolecular folding and assembly processes, but the computational demands of the underlying algorithms limit the lenth- and time-scales of the simulations one can perform. Recently, graphics processing units (GPUs), specialized devices that were originally designed for rendering images, have been repurposed for high performance computing, and there have been significant increases in the performances of parallel algorithms such as the ones in MD simulations. Previously, we implemented a GPU-optimized parallel neighbor list algorithm for our coarsegrained MD simulations, and we observed an N-dependent speed-up (or speed-down) compared to a CPU-optimized algorithm, where N is the number of interacting beads representing amino acids or nucleotides for proteins or RNAs, respectively. We had demonstrated that for MD simulations of the 70s ribosome (N=10,219), our GPU-optimized code was about 30x as fast as a CPU-optimized version. In our present study, we implement a hybrid neighbor/cell list algorithm that borrows components from the well-known neighbor list and the cell-list algorithms. We observe about 10% speedup as compared to our previous implementation of a GPU-optimized parallel neighbor list algorithm.