Abstract
When trying to gain retrospect on the papers presented in this workshop, one may notice that the borderline between compile-time and run-time is getting blurred in data dependence techniques, data placement, and the exploitation of parallelism. In other words, intensive research is being conducted to benefit from the best of both worlds so as to cope with real-size applications. This orientation is very encouraging and we can hope the end-user will soon benefit from the nice work proposed by the papers of this workshop.
Keywords
- Data Placement
- Cache Performance
- Dynamic Program Adaptability
- Automatic Parallelization
- Redundancy Elimination
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
P. Feautrier. Some efficient solutions to the affine scheduling problem, part I, one dimensional time. Int. J. of Parallel Programming, 21(5):313–348, October 1992.
J. Knoop, O. Rüthing, and B. Steffen. Optimal code motion: Theory and practice. ACM Transactions on Programming Languages and Systems, TOPLAS, 16:1117–1155, 1994.
Y. A. Liu. Dependence analysis for recursive data. In Int. Conf. on Computer Languages, pages 206–215, Chicago, Illinois, May 1998. IEEE.
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© 1998 Springer-Verlag Berlin Heidelberg
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Collard, JF. (1998). Workshop 04 automatic parallelization and high-performance compilers. In: Pritchard, D., Reeve, J. (eds) Euro-Par’98 Parallel Processing. Euro-Par 1998. Lecture Notes in Computer Science, vol 1470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0057883
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DOI: https://doi.org/10.1007/BFb0057883
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