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arXiv · 2311.02854

A distributed multi-GPU ab initio density matrix renormalization group algorithm with applications to the P-cluster of nitrogenase

Chunyang Xiang·Weile Jia·Wei-Hai Fang·Zhendong Li
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Abstract

The presence of many degenerate $d/f$ orbitals makes polynuclear transition metal compounds such as iron-sulfur clusters in nitrogenase challenging for state-of-the-art quantum chemistry methods. To address this challenge, we present the first distributed multi-GPU (Graphics Processing Unit) \emph{ab initio} density matrix renormalization (DMRG) algorithm, suitable for modern high-performance computing (HPC) infrastructures. The central idea is to parallelize the most computationally intensive part - the multiplication of $O(K^2)$ operators with a trial wavefunction, where $K$ is the number of spatial orbitals, by combining operator parallelism for distributing the workload with a batched algorithm for performing contractions on GPU. With this new implementation, we are able to reach an unprecedentedly large bond dimension $D=14000$ on 48 GPUs (NVIDIA A100 80 GB SXM) for an active space model (114 electrons in 73 active orbitals) of the P-cluster, which is nearly three times larger than the bond dimensions reported in previous DMRG calculations for the same system using only CPUs.

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Chunyang Xiang, Weile Jia, Wei-Hai Fang, Zhendong Li. 2023-12-21. A distributed multi-GPU ab initio density matrix renormalization group algorithm with applications to the P-cluster of nitrogenase. https://arxiv.org/abs/2311.02854

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