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Region analysis: a parallel elimination method for data flow analysis

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3 Author(s)
Lee, Y.-F. ; IBM Santa Teresa Lab. ; Ryder, B.G. ; Fiuczynski, M.E.

Parallel data flow analysis methods offer the promise of calculating detailed semantic information about a program at compile-time more efficiently than sequential techniques. Previous work on parallel elimination methods has been hampered by the lack of control over interval size; this can prohibit effective parallel execution of these methods. To overcome this problem, we have designed the region analysis method, a new elimination method for data flow analysis. Region analysis emphasizes flow graph partitioning to enable better load balancing in a more effective parallel algorithm. We present the design of region analysis and the empirical results we have obtained that indicate: the prevalence of large intervals in flow graphs derived from real programs; and the performance improvement of region analysis over parallel Allen-Cocke interval analysis. Our implementation analyzed programs from the Perfect Benchmarks and netlib running on a Sequent Symmetry S81

Published in:

Computer Languages, 1994., Proceedings of the 1994 International Conference on

Date of Conference:

16-19 May 1994