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A practical algorithm for exact array dependence analysis
Communications of the ACM
Fusion of Loops for Parallelism and Locality
IEEE Transactions on Parallel and Distributed Systems
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LAPACK Users' guide (third ed.)
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Loop tiling for parallelism
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ICPP '05 Proceedings of the 2005 International Conference on Parallel Processing
Merging compositions of array skeletons in SAC
Parallel Computing - Algorithmic skeletons
With-Loop fusion for data locality and parallelism
IFL'05 Proceedings of the 17th international conference on Implementation and Application of Functional Languages
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Existing loop fusion algorithms fuse loop nests only when the dependences in the loop nests are not violated. This paper presents a new algorithm that is capable of fusing loop nests in the presence of fusion-preventing anti-dependences. We eliminate all these violated dependences by automatic array copying. In this work, such an aggressive loop fusion strategy is applied to a Jacobi program. The performance of such iterative methods is typically limited by the speed of the memory system. Fusing the two loop nests in the Jacobi program into one reduces data cache misses, and consequently, improves the performance results of both sequential and parallel versions of the Jacobi program, as validated by our experimental results on an HP AlphaServer SC45 supercomputer.