RESEARCH AND DEVELOPMENT OF A PARALLELIZING COMPILER FOR ARBITRARY GRAIN SIZES AND GENERAL PARARLLEL ARCHITECTURES

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On top of the vectorizing compiler V-Pascal that had been developed by the Tsuda laboratory of Kyoto University over ten years, automatic parallelizing functions were added, together with various features. (1) Powerful ability to detect parallelism, (2) facility to find optimal grain sizes, (3) enhancing the locality of data references by means of data partitioning and loop transformation, and (3) minimizing machine-dependences in automatic parallelization by abstraction of parallel architectures are the main difficulties that remain to be resolved. In this project, new algorithms were developed for alias analyzes to have more precision in the analysis of dependeces due to pointer references. Alias analyzes in the presence of pointer variables that point to memory area that has been assigned by heap are especially difficult, but the result of this project gives an important clue to the problem. This partially answers the question (1) above. Concerning the question (2), a special view mechanism has been considered so that the results of dependence analyzes can be displayd at an arbitrary hierarchical level, namely, either coarse-grain level or fine-grain level. This makes it easier to check on, and choose, optimal parallelization.