Performance of heterogeneous computing with graphics processing unit and many integrated core for hartree potential calculations on a numerical grid

Abstract

We investigated the performance of heterogeneous computing with graphics processing units (GPUs) and many integrated core (MIC) with 20 CPU cores (20xCPU). As a practical example toward large scale electronic structure calculations using grid-based methods, we evaluated the Hartree potentials of silver nanoparticles with various sizes (3.1, 3.7, 4.9, 6.1, and 6.9 nm) via a direct integral method supported by the sinc basis set. The so-called work stealing scheduler was used for efficient heterogeneous computing via the balanced dynamic distribution of workloads between all processors on a given architecture without any prior information on their individual performances. 20xCPU+1GPU was up to approximate to 1.5 and approximate to 3.1 times faster than 1GPU and 20xCPU, respectively. 20xCPU+2GPU was approximate to 4.3 times faster than 20xCPU. The performance enhancement by CPU+MIC was considerably lower than expected because of the large initialization overhead of MIC, although its theoretical performance is similar with that of CPU+GPU. (c) 2016 Wiley Periodicals, Inc.