Abstract
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.
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Xue, J. (2005). Aggressive Loop Fusion for Improving Locality and Parallelism. In: Pan, Y., Chen, D., Guo, M., Cao, J., Dongarra, J. (eds) Parallel and Distributed Processing and Applications. ISPA 2005. Lecture Notes in Computer Science, vol 3758. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11576235_28
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DOI: https://doi.org/10.1007/11576235_28
Publisher Name: Springer, Berlin, Heidelberg
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