Time-dependent wavepackets are widely used to model various phenomena in physics. One approach in simulating the wavepacket dynamics is the quantum trajectory method (QTM). Based on the hydrodynamic formulation of quantum mechanics, the QTM represents the wavepacket by an unstructured set of pseudoparticles whose trajectories are coupled by the quantum potential. The governing equations for the pseudoparticle trajectories are solved using a computationally-intensive moving weighted least squares (MWLS) algorithm, and the trajectories can be computed in parallel. This work contributes a strategy for improving the performance of wavepacket simulations using the QTM on message-passing systems. Specifically, adaptivity is incorporated into the MWLS algorithm, and loop scheduling is employed to dynamically load balance the parallel computation of the trajectories. The adaptive MWLS algorithm reduces the amount of computations without sacrificing accuracy, while adaptive loop scheduling addresses the load imbalance introduced by the algorithm and the runtime system. Results of experiments on a Linux cluster are presented to confirm that the adaptive MWLS reduces the trajectory computation time by up to 24%, and adaptive loop scheduling achieves parallel effieciencies of up to 90% when simulating a free particle.
Message-Passing Parallel Adaptive Quantum Trajectory MethodHigh Performance Scientific and Engineering Computing
Document TypeContribution to Books
Citation InformationCarino, R. L., Banicescu, I., Vadapalli, R. K., Weatherford, C. A., and Zhu, J. (2004), Message passing parallel adaptive quantum trajectory method, in High Performance Scientific and Engineering Computing, 127 – 139, Yang and Pan Eds. Kluwer Academic Publisher, Norwell, MA.