Multi-GPU MBE(3)-OSV-MP2 for Performant Large-Scale ab initio Calculations
Qiujiang Liang, Jun Yang

TL;DR
This paper introduces a multi-GPU implementation of MBE(3)-OSV-MP2 for large-scale ab initio calculations, achieving significant speedups and enabling efficient computations on macromolecules.
Contribution
The authors develop a novel multi-GPU algorithm for MBE(3)-OSV-MP2, addressing GPU parallelization challenges in local correlation methods for large molecules.
Findings
Achieves $O(N^{1.9})$ scaling and 84% parallel efficiency on 24 GPUs.
Delivers 40-fold speedup over canonical RI-MP2 for large water clusters.
Completes large-scale insulin peptide calculations in minutes to hours on 8 GPUs.
Abstract
The computational acceleration of orbital-invariant local correlation methods on graphics processing units (GPUs) has remained largely unexplored due to substantial algorithmic complexities. The runtime efficiency of GPU-implemented local correlation theories can be significantly constrained by the parallelizable degree of the orbital localization procedure, the iterative solution of the local wave function, and the adaptation of CUDA kernels to inherently local or sparse operations. Using the second-order M{\o}ller-Plesset perturbation (MP2) theory, we present a multi-GPU implementation for large-scale third-order many-body expansion orbital-specific virtual MP2 (MBE(3)-OSV-MP2) energy calculations. Accordingly, our algorithms and implementation address the GPU parallelization ability for peak utilization and parallelism of local MP2 computation in several aspects, including…
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Taxonomy
TopicsProtein Structure and Dynamics · Advanced Chemical Physics Studies · Advanced NMR Techniques and Applications
