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Granularity analysis for exploiting adaptive parallelism of declarative programs on multiprocessors

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Abstract

Declarative Programming Languages (DPLs) apply a process model of Horn clauses such as PARLOG[8] or a reduction model of λ-calculus such as SML[7] and are, in principle, well suited to multiprocessor implementation. However, the performance of a parallel declarative program can be impaired by a mismatch between the parallelism available in an application and the parallelism available in the architecture. A particularly attractive solution is to automatically match the parallelism of the program to the parallelism of the target hardware as a compilation step. In this paper, we present an optimizing compilation technique called granularity analysis which identifies and removes excess parallelism that would degrade performance. The main steps are: an analysis of the flow of data to form an attributed call graph between function (or predicate) arguments; and an asymptotic estimation of granularity of a function (or predicate) to generate approximate grain size. Compiled procedure calls can be annotated with grain size and a task scheduler can make scheduling decisions with the classification scheme of grains to control parallelism at run-time. The resulting granularity analysis scheme is suitable for exploiting adaptive parallelism of declarative programming languages on multiprocessors.

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Authors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, 100084, Beijing

    Xinmin Tian, Dingxing Wang, Meiming Shen, Weimin Zheng & Dongchan Wen

Authors
  1. Xinmin Tian
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  2. Dingxing Wang
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  3. Meiming Shen
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  4. Weimin Zheng
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  5. Dongchan Wen
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Additional information

This work was partially supported by the National Natural Science Foundation of China under Grant 863-306-101 and the National Doctoral Subject Foundation under Grant 0249136.

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Tian, X., Wang, D., Shen, M. et al. Granularity analysis for exploiting adaptive parallelism of declarative programs on multiprocessors. J. of Compt. Sci. & Technol. 9, 144–152 (1994). https://doi.org/10.1007/BF02939495

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  • DOI: https://doi.org/10.1007/BF02939495

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