Abstract
Granularity is a well known concept in parallel processing. While intuitively, the distinction between coarse-grain and fine-grain paralellism is clear, there is no rigorous definition. This paper develops two notions of granularity, each defined formally and represented by a single rational number. The two notions are compared and contrasted with each other and with previously proposed definitions of granularity.
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References
Babb, R. G. II. 1984. Parallel processing with large-grain data flow techniques. IEEE Computer, 17, 7 (July), 55–61.
Baudet, G., and Stevenson, D. 1978. Optimal sorting algorithms for parallel computers. IEEE Transactions on Computers, C-27 (Jan.), 84–87.
Calahan, D. A. 1985. Task granularity studies on a many-processor CRAY X-MP. Parallel Computing, 2, 2 (June), 109–118.
Chen, S. S., Dongarra, J. J., and Hsiung, C. C. 1984. Multiprocessing linear algebra algorithms on the CRAY X-MP-2: Experiences with small granularity. Journal of Parallel and Distributed Computing, 1, 1, pp. 22–31.
Cole, R. 1986. Parallel merge sort. In Proceedings of the 27th Annual Symposium on the Foundations of Computer Science, (Oct.) pp. 511–516.
Cvetanovic, Z. 1987. The effects of problem partitioning, allocation, and granularity on the performance of multiple-processor systems. IEEE Transactions on Computers, C-36 (Apr.), 421–432.
Gottlieb, A., Grisham, R., Kruskal, C. P., McAuliffe, K. P., Rudolph, L., and Snir, M. 1983. The NYU Ultracomputer-Designing an MIMD shared-memory parallel computer. IEEE Transactions on Computers, C-32 (Feb.), 175–189.
Habermann, A. 1972. Parallel neighbor sort. Computer Science Report, Carnegie-Mellon University, Pittsburgh.
Halstead, B. 1984. The fine granularity working group report. Computer Architecture Technical Committee of the IEEE Computer Society, pp. 63–66.
Kruskal, C. P. 1983. Searching, merging, and sorting in parallel computation. IEEE Transactions on Computers, C-32 (Oct.), 942–946.
Kuck, D. J., Davidson, E. S., Lawrie, D. H., and Sameh, A. H. 1986. Parallel supercomputing today and the Cedar approach. Science, 281 (Feb. 28), 967–974.
Kung, H. T. 1985. Memory requirements for balanced computer architectures. Journal of Complexity, 1, 1 (Oct.), 147–157.
Lakshmivarahan, S., Dhall, S. K., and Miller, L. L. 1984. Parallel sorting algorithms. In Advances in Computers (M. C. Yovits, Ed.), Vol. 23. Academic Press, New York, pp. 295–354.
Lyon, G. 1987. On parallel processing benchmarks. National Bureau of Standards Report NBSIR 87-3580, June, 32pp.
Mohan, J. 1984. Performance of parallel programs: Model and analysis. Ph.D. dissertation, Carnegie-Mellon University, Pittsburgh.
Mohan, J., Jones, A., Gehringer, E., and Segall, Z. 1985. Granularity of parallel computation. In Proceedings of the 18th Hawaii International Conference on System Sciences, Vol. 3, Western Periodicals Co., pp. 249–256.
Pfister, G. F., Brantley, W. C., George, D. A., Harvey, S. L., Kleinfelder, W. J., McAuliffe, K. P., Melton, E. A., Norton, V. A., and Weiss, J. 1985. The IBM research parallel processor prototype (RP3): Introduction and architecture. In Proceedings of the International Conference on Parallel Processing (Aug.), IEEE Computer Society Press, pp. 764–771.
Rettberg, R., and Thomas, R. 1986. Contention is no obstacle to shared-memory multiprocessing. Communications of the ACM, 29, 12 (Dec.), 1202–1212.
Stone, H. S. 1987. High-performance Computer Architecture. Addison-Wesley, Reading, Mass.
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Supported, in part, by NSA OCREAE Grant MDA904-85-H-0002. Currently on leave at the National Science Foundation.
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Kruskal, C.P., Smith, C.H. On the notion of granularity. J Supercomput 1, 395–408 (1988). https://doi.org/10.1007/BF00128489
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DOI: https://doi.org/10.1007/BF00128489