Abstract
Sparse matrix problems are difficult to parallelize efficiently on message-passing machines, since they access data through multiple levels of indirection. Inspector/executor strategies, which are typically used to parallelize such problems impose significant preprocessing overheads. This paper describes the run-time support required by new compilation techniques for sparse matrices and evaluates their performance, highlighting optimizations and improvements over previous techniques.
This work was supported by the Ministry of Education and Science (CICYT) of Spain under project TIC92-0942 and by ONR under contracts No. SC 292-1-22913 and No. N000149410907, by NASA under contract No. NAG-11560 and by ARPA under contract No. NAG-11485. The authors assume all responsibility for the contents of the paper.
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References
R. Das, J. Saltz and R. von Hanxleden. Slicing Analysis and Indirect Access to Distributed Arrays, Proceedings of the 6th Workshop on Languages and Compilers for Parallel Computing, Aug 1993, pp 152–168. Also available as University of Maryland Technical Report CS-TR-3076 and UMIACS-TR-93-42.
R. Das, J. Saltz, K. Kennedy, P. Havlak. Index Array Flattening Through Program Transformations. Submitted to Supercomputing'95. San Diego, CA. Dic. 1995.
High Performance Language Specification. Version 1.0, Technical Report TR92-225, Rice University, May 3, 1993. Also available as Scientific Programming 2(1–2):1–170, Spring and Summer 1993.
A. Krishnamurthy, D.E. Culler, A. Dusseau, S.C. Goldstein, S. Lumetta, T. von Eicken, and K. Yelick. Parallel Programming in Split-C, Proceedings Supercomputing'93. Nov. 1993, pp 262–273.
P. Mehrotra and J. Van Rosendale. Programming distributed memory architectures using Kali. In A. Nicolau, D. Gelernter, T. Gross and D. Padua, editors, Advances in Languages and Compilers for Parallel Processing, pp. 364–384. Pitman/MIT-Press, 1991.
R. Mirchandaney, J. Saltz, R.M. Smith, D.M. Nicol and Kay Crowley. Principles of run-time support for parallel processors. Proceedings of the 1988 ACM International Conference on Supercomputing, pages 140–152, July, 1988.
S. D. Sharma, R. Ponnusamy, B. Moon, Y. Hwang, R. Das and J. Saltz. Runtime and Compile-time Support for Adaptive Irregular Problems, Proceedings Supercomputing '94, Nov. 1994, pp. 97–106.
M. Ujaldon and E.L. Zapata, Efficient Resolution of Sparse Indirections in Data-Parallel Compilers. Proceedings of the 9th ACM International Conference on Supercomputing. Barcelona (Spain), July 1995 (to appear).
M. Ujaldon, E. L. Zapata, B. Chapman and H. Zima. Vienna-Fortran/HPF Extensions for Sparse and Irregular Problems and their Compilation, Submitted to IEEE Transactions on Parallel and Distributed Systems. Also available as Technical Report.
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Ujaldon, M., Sharma, S.D., Saltz, J., Zapata, E.L. (1995). Run-time techniques for parallelizing sparse matrix problems. In: Ferreira, A., Rolim, J. (eds) Parallel Algorithms for Irregularly Structured Problems. IRREGULAR 1995. Lecture Notes in Computer Science, vol 980. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60321-2_3
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DOI: https://doi.org/10.1007/3-540-60321-2_3
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