Publication | Open Access
Coupled Cluster Theory on Graphics Processing Units I. The Coupled Cluster Doubles Method
121
Citations
32
References
2011
Year
Cluster ComputingEngineeringGpu BenchmarkingElectronic CorrelationComputer Graphic TechniqueCc EquationsComputer ArchitectureComputational ChemistryGpu ComputingCluster TechnologyGraphics Processing UnitsParallel ComputingComputational GeometryGeometric ModelingPhysicsComputer EngineeringComputer ScienceQuantum ChemistryGpu ClusterComputational ScienceGpu ArchitectureHardware AccelerationCluster DevelopmentNatural SciencesCc IterationCluster TheoryParallel Programming
The coupled cluster (CC) ansatz is generally recognized as providing one of the best wave function-based descriptions of electronic correlation in small- and medium-sized molecules. The fact that the CC equations with double excitations (CCD) may be expressed as a handful of dense matrix-matrix multiplications makes it an ideal method to be ported to graphics processing units (GPUs). We present our implementation of the spin-free CCD equations in which the entire iterative procedure is evaluated on the GPU. The GPU-accelerated algorithm readily achieves a factor of 4-5 speedup relative to the multithreaded CPU algorithm on same-generation hardware. The GPU-accelerated algorithm is approximately 8-12 times faster than Molpro, 17-22 times faster than NWChem, and 21-29 times faster than GAMESS for each CC iteration. Single-precision GPU-accelerated computations are also performed, leading to an additional doubling of performance. Single-precision errors in the energy are typically on the order of 10(-6) hartrees and can be improved by about an order of magnitude by performing one additional iteration in double precision.
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