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Performance of Coupled-Cluster Singles and Doubles on Modern Stream Processing Architectures

B. Scott Fales, Ethan R. Curtis, K. Grace Johnson, Dean Lahana, Stefan Seritan, Yuanheng Wang, Hayley Weir, Todd J. Martı́nez, Edward G. Hohenstein

2020Journal of Chemical Theory and Computation30 citationsDOI

Abstract

We develop a new implementation of coupled-cluster singles and doubles (CCSD) optimized for the most recent graphical processing unit (GPU) hardware. We find that a single node with 8 NVIDIA V100 GPUs is capable of performing CCSD computations on roughly 100 atoms and 1300 basis functions in less than 1 day. Comparisons against massively parallel implementations of CCSD suggest that more than 64 CPU-based nodes (each with 16 cores) are required to match this performance.

Topics & Concepts

Computer scienceCoupled clusterComputationGPU clusterComputational scienceParallel computingNode (physics)Graphics processing unitCluster (spacecraft)Massively parallelCentral processing unitImplementationCUDAAlgorithmComputer hardwarePhysicsOperating systemQuantum mechanicsMoleculeProgramming languageCloud Computing and Resource ManagementCaching and Content DeliveryComplex Network Analysis Techniques
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