| Summary: | 碩士 === 國立交通大學 === 資訊科學學系 === 82 === More and more popular multiprocessor architectures have made
traditional compiling methodology insufficient. For this
reason, various parallelizing compiling techniques have been
developed to exploit the potential parallelism. Although none
of the new methods is suitable for all input cases, each has
its own advantages over other ones. This motivates us to study
the feasibility of integrating these techniques by knowledge-
based approaches. In this thesis, we concentrate on the
fundamental phase, data dependence analysis, in parallelizing
compilers. We propose a new approach which integrates existing
tests and makes good use of their advantages. This approach
chooses an appropriate test by knowledge-based methodology, and
then applies the resulting test to detect data dependence on
loops. A rule-based system, called the K test, is developed by
repertory grid analysis to construct the knowledge base.
Simulation results show that the K test gives relatively exact
solutions in both practical and contrived cases; furthermore,
as for system maintenance and extendibility, our approach is
obviously superior to others. Therefore, we are trying to
extend the knowledge-based approach to the whole field of
parallelizing compiling.
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