2000IEEE Transactions on Software EngineeringRequires access

Efficient interprocedural array data-flow analysis for automatic program parallelization

Junjie Gu, Zhiyuan Li

Open publisher page 12 citations

Abstract

Since sequential languages such as Fortran and C are more machine-independent than current parallel languages, it is highly desirable to develop powerful parallelization tools which can generate parallel codes, automatically or semi-automatically, targeting different parallel architectures. Array data-flow analysis is known to be crucial to the success of automatic parallelization. Such an analysis should be performed interprocedurally and symbolically and it often needs to handle the predicates represented by IF conditions. Unfortunately, such a powerful program analysis can be extremely time-consuming if it is not carefully designed. How to enhance the efficiency of this analysis to a practical level remains an issue largely untouched to date. This paper presents techniques for efficient interprocedural array data-flow analysis and documents experimental results of its implementation in a research parallelizing compiler. Our techniques are based on guarded array regions and the resulting tool runs faster, by one or two orders of magnitude, than other similarly powerful tools.

About this research paper

What this paper is about

Since sequential languages such as Fortran and C are more machine-independent than current parallel languages, it is highly desirable to develop powerful parallelization tools which can generate parallel codes, automatically or semi-automatically, targeting different parallel architectures. Array data-flow analysis is known to be crucial to the success of automatic parallelization. Such an analysis should be performed interprocedurally and symbolically and it often needs to handle the predicates represented by IF conditions. Unfortunately, such a powerful program analysis can be extremely time-consuming if it is not carefully designed. How to enhance the efficiency of this analysis to a practical level remains an issue largely untouched to date. This paper presents techniques for efficient interprocedural array data-flow analysis and documents experimental results of its implementation in a research parallelizing compiler. Our techniques are based on guarded array regions and the resulting tool runs faster, by one or two orders of magnitude, than other similarly powerful tools.

Why it matters

OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Since sequential languages such as Fortran and C are more machine-independent than current parallel languages, it is highly desirable to develop powerful parallelization tools which can generate parallel codes, automatically or semi-automatically, targeting different parallel architectures. Array data-flow analysis is known to be crucial to the success of automatic parallelization. Such an analysis should be performed interprocedurally and symbolically and it often needs to handle the predicates represented by IF conditions. Unfortunately, such a powerful program analysis can be extremely time-consuming if it is not carefully designed. How to enhance the efficiency of this analysis to a practical level remains an issue largely untouched to date. This paper presents techniques for efficient interprocedural array data-flow analysis and documents experimental results of its implementation in a research parallelizing compiler. Our techniques are based on guarded array regions and the resulting tool runs faster, by one or two orders of magnitude, than other similarly powerful tools.

Key concepts: Computer science, Automatic parallelization, Compiler, Parallel computing, Data-flow analysis, Programming language, Fortran, Dependence analysis

Related papers

Back to paper searchBrowse research topicsOriginal source
Efficient interprocedural array data-flow analysis for automatic program parallelization — Research Paper | ScholarLens