NDLI: Efficient techniques for advanced data dependence analysis

Content Provider	IEEE Xplore Digital Library
Author	Kyriakopoulos, K. Psarris, K.
Copyright Year	2005
Description	Author affiliation: Dept. of Comput. Sci., Texas Univ., San Antonio, TX, USA (Kyriakopoulos, K.; Psarris, K.)
Abstract	Scientific source code for high performance computers is extremely complex containing irregular control structures with complicated expressions. This complexity makes it difficult for compilers to analyze the code and perform optimizations. In particular with regard to program parallelization, complex expressions are often not taken intro consideration during the data dependence analysis phase. In this work we propose new data dependence analysis techniques to handle such complex instances of the dependence problem and increase program parallelization. Our method is based on a set of polynomial time techniques that can prove or disprove dependences in the presence of non-linear expressions, complex loop bounds, arrays with coupled subscripts, and if statement constraints. In addition our algorithm can produce accurate and complete direction vector information enabling the compiler to apply further transformations. To validate our method we performed an experimental evaluation and comparison against the I-Test, the Omega test and the Range test in the Perfect and SPEC benchmarks. The experimental results indicate that our dependence analysis tool is efficient and more effective in program parallelization than the other dependence tests. The improved parallelization of key loops results into higher speedups and better program execution performance in several benchmarks.
Starting Page	143
Ending Page	153
File Size	227329
Page Count	11
File Format	PDF
ISBN	076952429X
ISSN	1089795X
DOI	10.1109/PACT.2005.19
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data analysis Optimizing compilers Benchmark testing Polynomials Computer science High performance computing Performance analysis Performance evaluation Algorithm design and analysis Couplings
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Hardware and Architecture Software

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