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A Heuristic Rule of Partitioning Irregular Loop for Parallelizing Compilers

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High Performance Computing and Applications

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5938))

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Abstract

For irregular applications on distributed-memory systems, computation partition is an important issue on parallel compiling techniques of parallelizing compilers. In this paper, we propose a local optimal solution, called heuristic computes rule (HCR), which could be used for irregular loop partitioning. This rule considers both the iteration being partitioned and the iterations partitioned, which ensures that iterations are assigned so as to produce less communication costs. And HCR rule proposes that irregular loop partitioning should trade off the maximum message degrees of processors, the number of messages, the message sizes, and workload balance. In our experiments, we compare HCR with almost owner computes rule and least communication computes rule. The results show that the executing of irregular loop partitioned by HCR rule has much less communication cost and achieve better performance.

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References

  1. Rauchwerger, L.: Run-time parallelization: It’s time has come. Journal of Parallel Computing, Special Issue on Languages and Compilers for Parallel Computers 24, 527–556 (1998)

    MATH  Google Scholar 

  2. Lin, Y.: Compiler analysis of sparse and irregular computations. University of Illinois at Urbana-Champaign (2000)

    Google Scholar 

  3. Ponnusamy, R., Hwang, Y.S., Das, R., Saltz, J., Choudhary, A., Fox, G.: Supporting irregular distributions in FORTRAN 90D/HPF compilers. University of Maryland, Department of Computer Science and UMIACS (1994)

    Google Scholar 

  4. Guo, M., Li, L., Chang, W.L.: Efficient loop partitioning for parallel codes of irregular scientific computations. In: Fifth International Conference on Algorithms and Architectures for Parallel Processing, pp. 60–70. IEEE Computer Society, Los Alamitos (2002)

    Google Scholar 

  5. Chakrabarti, S., Gupta, M., Choi, J.D.: Global communication analysis and optimization. ACM SIGPLAN Notices 31, 68–78 (1996)

    Article  Google Scholar 

  6. Chavarría-Miranda, D., Mellor-Crummey, J.: Effective communication coalescing for data-parallel applications. In: Proc. the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming, pp. 14–25. ACM, New York (2005)

    Google Scholar 

  7. Guo, M., Cao, J., Chang, W.L., Li, L., Liu, C.: Effective OpenMP Extensions for Irregular Applications on Cluster Environments. LNCS, pp. 97–104. Springer, Heidelberg (2004)

    Google Scholar 

  8. Stone, J.M., Norman, M.L.: ZEUS-2 D: A radiation magnetohydrodynamics code for astrophysical flows in two space dimensions: the hydrodynamic algorithms and tests. Astrophysical Journal Supplement Series 80, 753–790 (1992)

    Article  Google Scholar 

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Hu, C., Liu, Y., Wang, J., Li, J. (2010). A Heuristic Rule of Partitioning Irregular Loop for Parallelizing Compilers. In: Zhang, W., Chen, Z., Douglas, C.C., Tong, W. (eds) High Performance Computing and Applications. Lecture Notes in Computer Science, vol 5938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11842-5_23

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  • DOI: https://doi.org/10.1007/978-3-642-11842-5_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11841-8

  • Online ISBN: 978-3-642-11842-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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