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Improved Preprocessing Methods for Modulo Scheduling Algorithms

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High Performance Computing — HiPC 2002 (HiPC 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2552))

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Abstract

Instruction scheduling with an automaton-based resource conflict model is well-established for normal scheduling. Such models have been generalized to software pipelining in the modulo-scheduling framework. One weakness with existing methods is that a distinct automaton must be constructed for each combination of a reservation table and initiation interval. In this work, we present a different approach to model conflicts. We construct one automaton for each reservation table which acts as a compact encoding of all the conflict automata for this table, which can be recovered for use in modulo-scheduling. The basic premise of the construction is to move away from the Proebsting-Fraser model of conflict automaton to the Müller model of automaton modelling issue sequences. The latter turns out to be useful and efficient in this situation. Having constructed this automaton, we show how to improve the estimate of resource constrained initiation interval. Such a bound is always better than the average-use estimate. We show that our bound is safe: it is always lower than the true initiation interval. This use of the automaton is orthogonal to its use in modulo-scheduling. Once we generate the required information during pre-processing, we can compute the lower bound for a program without any further reference to the automaton.

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References

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© 2002 Springer-Verlag Berlin Heidelberg

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Ravindra, D.V., Srikant, Y.N. (2002). Improved Preprocessing Methods for Modulo Scheduling Algorithms. In: Sahni, S., Prasanna, V.K., Shukla, U. (eds) High Performance Computing — HiPC 2002. HiPC 2002. Lecture Notes in Computer Science, vol 2552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36265-7_46

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  • DOI: https://doi.org/10.1007/3-540-36265-7_46

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00303-8

  • Online ISBN: 978-3-540-36265-4

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