Optimization of array redistribution for distributed memory multicomputers
Parallel Computing
Optimizations for efficient array redistribution on distributed memory multicomputers
Journal of Parallel and Distributed Computing - Special issue on compilation techniques for distributed memory systems
Contention-free communication scheduling for array redistribution
Parallel Computing
Processor reordering algorithms toward efficient GEN_BLOCK redistribution
Proceedings of the 2001 ACM symposium on Applied computing
A Generalized Processor Mapping Technique for Array Redistribution
IEEE Transactions on Parallel and Distributed Systems
Symbolic Communication Set Generation for Irregular Parallel Applications
The Journal of Supercomputing
A Divide-and-Conquer Algorithm for Irregular Redistribution in Parallelizing Compilers
The Journal of Supercomputing
An efficient algorithm for irregular redistributions in parallelizing compilers
ISPA'03 Proceedings of the 2003 international conference on Parallel and distributed processing and applications
Optimal processor mapping scheme for efficient communication of data realignment
ISPA'04 Proceedings of the Second international conference on Parallel and Distributed Processing and Applications
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The data redistribution problems on multi-computers had been extensively studied. Irregular data redistribution has been paid attention recently since it can distribute different size of data segment of each processor to processors according to their own computation capability. High Performance Fortran Version 2 (HPF-2) provides GEN_BLOCK data distribution method for generating irregular data distribution. In this paper, we develop an efficient scheduling algorithm, Smallest Conflict Points Algorithm (SCPA), to schedule HPF2 irregular array redistribution. SCPA is a near optimal scheduling algorithm, which satisfies the minimal number of steps and minimal total messages size of steps for irregular data redistribution.