Noniterative Multireference Coupled Cluster Methods on Heterogeneous CPU-GPU Systems.

A novel parallel algorithm for noniterative multireference coupled cluster (MRCC) theories, which merges recently introduced reference-level parallelism (RLP) [Bhaskaran-Nair, K.; Brabec, J.; Aprà, E.; van Dam, H. J. J.; Pittner, J.; Kowalski, K. J. Chem. Phys.2012, 137, 094112] with the possibility of accelerating numerical calculations using graphics processing units (GPUs) is presented. We discuss the performance of this approach applied to the MRCCSD(T) method (iterative singles and doubles and perturbative triples), where the corrections due to triples are added to the diagonal elements of the MRCCSD effective Hamiltonian matrix. The performance of the combined RLP/GPU algorithm is illustrated on the example of the Brillouin-Wigner (BW) and Mukherjee (Mk) state-specific MRCCSD(T) formulations.

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