Summary
Data and computation alignment is an important part of compiling sequential programs to architectures with non-uniform memory access times. In this paper, we show that elementary matrix methods can be used to determine communication-free alignment of code and data. We also solve the problem of replicating data to eliminate communication. Our matrix-based approach leads to algorithms which work well for a variety of applications, and which are simpler and faster than other matrix-based algorithms in the literature.
An earlier version of this paper was presented in the 7th Annual Workshop on Languages and Compilers for Parallel Computers (LCPC), Ithaca, 1994.
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Kotlyar, V., Bau, D., Kodukula, I., Pingali, K., Stodghill, P. (2001). Solving Alignment Using Elementary Linear Algebra. In: Pande, S., Agrawal, D.P. (eds) Compiler Optimizations for Scalable Parallel Systems. Lecture Notes in Computer Science, vol 1808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45403-9_11
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DOI: https://doi.org/10.1007/3-540-45403-9_11
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