Scalable Heterogeneous Execution of a Coupled-Cluster Model with Perturbative Triples

被引:3
|
作者
Kim, Jinsung [1 ]
Panyala, Ajay [2 ]
Peng, Bo [3 ]
Kowalski, Karol [3 ]
Sadayappan, P. [1 ]
Krishnamoorthy, Sriram [2 ]
机构
[1] Univ Utah, Sch Comp, Salt Lake City, UT 84112 USA
[2] Pacific Northwest Natl Lab, High Performance Comp, Richland, WA 99352 USA
[3] Pacific Northwest Natl Lab, Chem Phys & Anal, Richland, WA 99352 USA
关键词
FULL CCSDT MODEL; PARALLEL IMPLEMENTATION; FRAMEWORK; PERFORMANCE; ENERGIES; SYSTEMS; LIMIT; MP2;
D O I
10.1109/SC41405.2020.00083
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 3.4x. Finally, we discuss the trade-offs in using this fused algorithm on current and future supercomputing platforms.
引用
收藏
页数:15
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