Performance of heterogeneous computing with graphics processing unit and many integrated core for hartree potential calculations on a numerical grid. Issue 24 (19th July 2016)

• Record Type: Journal Article
• Authors: Choi, Sunghwan; Kwon, Oh‐Kyoung; Kim, Jaewook; Kim, Woo Youn
• Is Part Of: Journal of computational chemistry. Volume 37:Issue 24(2016)
• Page Start: 2193
• Page End: 2201
• Publication Date: 2016-07-19
• Subjects: density functional theory -- Hartree potential -- heterogeneous computing -- graphics processing unit -- many integrated core; Chemistry -- Data processing -- Periodicals; 542.85
• DOI: 10.1002/jcc.24443
• Languages: English
• ISSNs: 0192-8651

Abstract

Abstract : We investigated the performance of heterogeneous computing with graphics processing units (GPUs) and many integrated core (MIC) with 20 CPU cores (20×CPU). 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. 20×CPU + 1GPU was up to ∼1.5 and ∼3.1 times faster than 1GPU and 20×CPU, respectively. 20×CPU + 2GPU was ∼4.3 times faster than 20×CPU. 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. © 2016 Wiley Periodicals, Inc. Abstract : Grid‐based electronic structure calculations can be maximally accelerated on a modern computer architecture that combines between graphics processing units (GPUs) and central processing units. We compare the performance of heterogeneous computing between GPUs and many integrated cores for Hartree potential evaluations for silver nanoparticles with various sizes (3.1 to 6.9 nm). In particular, we use the work stealing scheduler for dynamically balanced task distribution between processors with different computing powers.