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Scalable heterogeneous execution of a coupled-cluster model with perturbative triples
- Kim, J.;
- Panyala, A.;
- Peng, B.;
- Kowalski, K.;
- Sadayappan, P.;
- 외 1명
SCOPUS
8초록
The CCSD(T) coupled-cluster model with perturbative triples is considered a gold standard for computational modeling of the correlated behavior of electrons in molecular systems. A fundamental constraint is the relatively small global-memory capacity in GPUs compared to the main-memory capacity on host nodes, necessitating relatively smaller tile sizes for high-dimensional tensor contractions in NWChem's GPU-accelerated implementation of the CCSD(T) method. A coordinated redesign is described to address this limitation and associated data movement overheads, including a novel fused GPU kernel for a set of tensor contractions, along with inter-node communication optimization and data caching. The new implementation of GPU-accelerated CCSD(T) improves overall performance by ;3.4 ×. Finally, we discuss the trade-offs in using this fused algorithm on current and future supercomputing platforms. © 2020 IEEE.
- 제목
- Scalable heterogeneous execution of a coupled-cluster model with perturbative triples
- 저자
- Kim, J.; Panyala, A.; Peng, B.; Kowalski, K.; Sadayappan, P.; Krishnamoorthy, S.
- 발행일
- 2020-11
- 유형
- Conference Paper
- 저널명
- International Conference for High Performance Computing, Networking, Storage and Analysis, SC
- 언어
- ENG
- 출판사
- IEEE Computer Society
- 발행국가
- 미국
- ISSN
- P 2167-4329