Faster Self-Consistent Field (SCF) Calculations on GPU Clusters

A novel implementation of the self-consistent field (SCF) procedure specifically designed for high-performance execution on multiple graphics processing units (GPUs) is presented. The algorithm offloads to GPUs the three major computational stages of the SCF, namely, the calculation of one-electron integrals, the calculation and digestion of electron repulsion integrals, and the diagonalization of the Fock matrix, including SCF acceleration via DIIS. Performance results for a variety of test molecules and basis sets show remarkable speedups with respect to the state-of-the-art parallel GAMESS CPU code and relative to other widely used GPU codes for both single and multi-GPU execution. The new code outperforms all existing multi-GPU implementations when using eight V100 GPUs, with speedups relative to Terachem ranging from 1.2X to 3.3X and speedups of up to 28X over QUICK on one GPU and 15x using eight GPUs. Strong scaling calculations show nearly ideal scalability up to 8 GPUs while retaining high parallel efficiency for up to 18 GPUs.

Automated summary

The novel implementation of the self-consistent field (SCF) procedure is specifically designed for high-performance execution on multiple graphics processing units (GPUs), showing remarkable speedups for various test molecules and basis sets compared to existing GPU codes. Strong scaling calculations demonstrate nearly ideal scalability up to 8 GPUs while maintaining high parallel efficiency for up to 18 GPUs.