GPGPU for orbital function evaluation with a new updating scheme

TL;DR

This paper demonstrates a GPGPU-accelerated ab-initio QMC electronic structure calculation with a novel updating scheme, achieving significant speedup and maintaining accuracy.

Contribution

It introduces a new quasi-simultaneous updating scheme for Monte Carlo sampling that improves GPGPU performance in electronic structure calculations.

Findings

30.8 times faster evaluation on TiO2 solid

Energy deviation within 10^{-3} hartree per primitive cell

Effective GPGPU implementation of spline basis set expansions

Abstract

We accelerated an {\it ab-initio} QMC electronic structure calculation by using GPGPU. The bottleneck of the calculation for extended solid systems is replaced by CUDA-GPGPU subroutine kernels which build up spline basis set expansions of electronic orbital functions at each Monte Carlo step. We achieved 30.8 times faster evaluation for the bottleneck, confirmed on the simulation of TiO$_2$ solid with 1,536 electrons. To achieve better performance in GPGPU we propose a new updating scheme for Monte Carlo sampling, quasi-simultaneous updating, which is in between the configuration-by-configuration updating and the widely-used particle-by-particle one. The energy deviation caused both by the single precision treatment and the new updating scheme is found to be within the accuracy required in the calculation, $\sim 10^{-3}$ hartree per primitive cell.