Multi-GPU MBE(3)-OSV-MP2 for Performant Large-Scale Ab Initio Calculations

High Resolution Image Download MS PowerPoint Slide 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 degree of parallelism in 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 Møller–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 to maximize peak utilization and the parallelism of local MP2 computation in several aspects, including Jacobi–Pipek–Mezey localization, randomized OSV (rOSV) generation, direct MP2 integral regeneration, and CUDA kernel adaptation for local operations. The GPU-based MBE(3)-OSV-MP2 energy computation achieves an effective empirical N 1.9 scaling up to (Gly) 40 /def2-TZVP and 84% parallel efficiency without localization up to 24 GPUs distributed on multiple nodes. The present implementation delivers 40-fold wall time speedup of the canonical RI-MP2 and 10-fold speedup of the central processing units (CPU)-based MBE(3)-OSV-MP2 for (H 2 O) 128 /cc-pVDZ and (H 2 O) 190 /cc-pVDZ, respectively. A large-scale computation of a 784-atom insulin peptide yields the full MBE(3)-OSV-MP2 energies in 24 min with cc-pVDZ (7571 basis functions) and in 6.4 h with cc-pVTZ (17,448 basis functions) on 8 NVIDIA A800 GPUs. Our work opens new possibilities for fast GPU-based local correlation calculations on real-world macromolecules.