Scalable heterogeneous execution of a coupled-cluster model with perturbative triples

  • Kim, J.; 
  • Panyala, A.; 
  • Peng, B.; 
  • Kowalski, K.; 
  • Sadayappan, P.; 
  • 외 1명
Citations

SCOPUS

8

초록

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.
DOI
10.1109/SC41405.2020.00083
발행일
2020-11
유형
Conference Paper
저널명
International Conference for High Performance Computing, Networking, Storage and Analysis, SC