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

Giuseppe M.J. Barca, Melisa Alkan, Jorge L. Galvez-Vallejo, David L. Poole, Alistair P. Rendell, Mark S. Gordon

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


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 1.2× to 3.3× and speedups of up to 28× over QUICK on one GPU and 15× using eight GPUs. Strong scaling calculations show nearly ideal scalability up to 8 GPUs while retaining high parallel efficiency for up to 18 GPUs.

Original languageEnglish
Pages (from-to)7486-7503
Number of pages18
JournalJournal of Chemical Theory and Computation
Issue number12
Early online date15 Nov 2021
Publication statusPublished - 14 Dec 2021


  • graphics processing units (GPUs)
  • self-consistent field (SCF)
  • one-electron integrals
  • electron repulsion integrals
  • Fock matrix


Dive into the research topics of 'Faster Self-Consistent Field (SCF) Calculations on GPU Clusters'. Together they form a unique fingerprint.

Cite this