Optimization of array redistribution for distributed memory multicomputers
Parallel Computing
Fast runtime block cyclic data redistribution on multiprocessors
Journal of Parallel and Distributed Computing
Efficient Algorithms for Block-Cyclic Array Redistribution Between Processor Sets
IEEE Transactions on Parallel and Distributed 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
A Framework for Efficient Data Redistribution on Distributed Memory Multicomputers
The Journal of Supercomputing
Sparse Matrix Block-Cyclic Redistribution
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
Multi-phase array redistribution: modeling and evaluation
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
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
PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies
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Runtime data alignment has been paid attention recently since it can allocate data segment to processors dynamically according to applications’ requirement. One of the key optimizations of this problem is to schedule simultaneous communications to avoid contention and to minimize the overall communication costs. The NP-completeness of the problem has instigated researchers to propose different heuristic algorithms. In this paper, we present an algorithm independent technique for optimizing scheduling stability of different scheduling heuristics. The proposed technique introduces a new scheduling policy, Local Message Reduction (LMR), to obtain better communication schedule adaptive to different environments. o evaluate the performance of the proposed technique, we have implemented LMR along with two existing algorithms, the two-phase degree reduction and the list scheduling algorithms. The experimental results show that the proposed technique is effective in terms of scheduling stability, communication efficiency and easy to implement.