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Advanced Techniques for High-Performance Fock Matrix Construction on GPU Clusters

arXiv
Authors: Elise Palethorpe, Ryan Stocks, Giuseppe M. J. Barca

Year

2024

Paper ID

64792

Status

Preprint

Abstract Read

~2 min

Abstract Words

195

Citations

N/A

Abstract

This Article presents two optimized multi-GPU algorithms for Fock matrix construction, building on the work of Ufimtsev et al. and Barca et al. The novel algorithms, opt-UM and opt-Brc, introduce significant enhancements, including improved integral screening, exploitation of sparsity and symmetry, a linear scaling exchange matrix assembly algorithm, and extended capabilities for Hartree-Fock caculations up to f-type angular momentum functions. Opt-Brc excels for smaller systems and for highly contracted triple-ζ basis sets, while opt-UM is advantageous for large molecular systems. Performance benchmarks on NVIDIA A100 GPUs show that our algorithms in the EXtreme-scale Electronic Structure System (EXESS), when combined, outperform all current GPU and CPU Fock build implementations in TeraChem, QUICK, GPU4PySCF, LibIntX, ORCA, and Q-Chem. The implementations were benchmarked on linear and globular systems and average speed ups across three double-ζ basis sets of 1.5times, 5.2times, and 8.5times were observed compared to TeraChem, GPU4PySCF, and QUICK respectively. Strong scaling analysis reveals over 91% parallel efficiency on four GPUs for opt-Brc, making it typically faster for multi-GPU execution. Single-compute-node comparisons with CPU-based software like ORCA and Q-Chem show speedups of up to 42times and 31times, respectively, enhancing power efficiency by up to 18times.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2024 reference point for readers tracking recent quantum research.
  • This Article presents two optimized multi-GPU algorithms for Fock matrix construction, building on the work of Ufimtsev et al.

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