Distributed Processing and A Vectorization Technique at Object Code Level


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 5, No. 5, pp. 1172-1184, May. 1998
10.3745/KIPSTE.1998.5.5.1172,   PDF Download:

Abstract

ILP(Instruction Level Parallelism) processors use code reordering algorithms to expose parallelism in a given sequential program. When applied to a loop, this algorithm produces a software-pipelined loop. In a software-pipelined loop, each iteration contains a sequence of parallel instructions that are composed of data-independent instructions collected across from several iterations. For vector loops, however the software pipelining technique can not expose the maximum parallelism because it schedules the program based only on data-dependencies. This paper proposes to schedule differently for vector loops. We develop an algorithm to detect vector loops at object code level and suggest a new vector scheduling algorithm for them. Our vector scheduling improves the performance because it can schedule not only based on data-dependencies but on loop structure or iteration conditions at the object code level. We compare the resulting schedules with those by software-pipelining techniques in the aspect of performance.


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Cite this article
[IEEE Style]
L. D. Hoo and K. K. Chang, "Distributed Processing and A Vectorization Technique at Object Code Level," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 5, no. 5, pp. 1172-1184, 1998. DOI: 10.3745/KIPSTE.1998.5.5.1172.

[ACM Style]
Lee Dong Hoo and Kim Ke Chang. 1998. Distributed Processing and A Vectorization Technique at Object Code Level. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 5, 5, (1998), 1172-1184. DOI: 10.3745/KIPSTE.1998.5.5.1172.