GPU acceleration of plane-wave density functional theory calculations in Abinit

Abstract

We report on the GPU port of the Abinit high-performance simulation code for plane-wave DFT calculations. Large-scale electronic structure calculations require computing the electronic wave function by solving the Kohn-Sham equations discretized over a large number of plane waves. Porting such calculations to GPU nodes relies not only on extensive usage of vendor libraries from a development perspective, but also on algorithmic revisions of the iterative diagonalization procedure in the resolution of the Kohn-Sham equations to identify GPU-efficient mathematical operations (linear algebra, FFTs) applied to the wave function distributed in memory. The present contribution discusses the Abinit implementation on multi-GPU architectures, providing detailed performance results for heterogeneous CPU-GPU nodes versus CPU nodes. Particular attention is given to comparing two diagonalization algorithms -- Locally Optimal Block Preconditioned Conjugate Gradient and Chebyshev polynomial filtering -- in terms of GPU efficiency.