Allocating Independent Subtasks on Parallel Processors
IEEE Transactions on Software Engineering
Guided self-scheduling: A practical scheduling scheme for parallel supercomputers
IEEE Transactions on Computers
Factoring: a method for scheduling parallel loops
Communications of the ACM
Balancing processor loads and exploiting data locality in N-body simulations
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Load-sharing in heterogeneous systems via weighted factoring
Proceedings of the eighth annual ACM symposium on Parallel algorithms and architectures
Dynamic Scheduling Parallel Loops with Variable Iterate Execution Times
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Load Balancing Highly Irregular Computations with the Adaptive Factoring
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Performance of Scheduling Scientific Applications with Adaptive Weighted Factoring
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
A Load Balancing Tool for Distributed Parallel Loops
CLADE '03 Proceedings of the 1st International Workshop on Challenges of Large Applications in Distributed Environments
Overhead Analysis of a Dynamic Load Balancing Library for Cluster Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 1 - Volume 02
Simulation of Vector Nonlinear Time Series Models on Clusters
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 13 - Volume 14
Design and implementation of a novel dynamic load balancing library for cluster computing
Parallel Computing - Heterogeneous computing
A Load Balancing Tool for Distributed Parallel Loops
Cluster Computing
Vector nonlinear time-series analysis of gamma-ray burst datasets on heterogeneous clusters
Scientific Programming - International Symposium of Parallel and Distributed Computing & International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogenous Networks
Dynamic load balancing with adaptive factoring methods in scientific applications
The Journal of Supercomputing
Performance evaluation of a dynamic load-balancing library for cluster computing
International Journal of Computational Science and Engineering
Investigating asymptotic properties of vector nonlinear time series models
Journal of Computational and Applied Mathematics
Computational challenges in vector functional coefficient autoregressive models
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
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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.