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
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
Cluster Computing
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A number of packages have recently been developed to enable the execution of MATLAB programs on parallel processors. For many applications, an integrated load balancing functionality is also necessary to realize the full benefits of parallelization. This paper describes a toolkit based on MatlabMPI to ease the parallelization and integration of load balancing into MATLAB applications that contain computationally-intensive loops with independent iterations. Modifications to existing code to incorporate the toolkit are minimal. Performance tests of two nontrivial MATLAB programs with the toolkit on a general-purpose Linux cluster indicate that significant speedups are achievable.