A Neural Network Based Tool for Semi-automatic Code Transformation
VECPAR '00 Selected Papers and Invited Talks from the 4th International Conference on Vector and Parallel Processing
An exact data dependence testing method for quadratic expressions
Information Sciences: an International Journal
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Several multiprocessor systems are now commercially available, and advances in compiler technology provide automatic conversion of programs to run on such systems. However, no accepted measure of this parallel compiler ability exists. This paper presents a test suite of subroutines and loops, called Parallel Loops, designed to (1) measure the ability of parallelizing compilers to convert code to run in parallel and (2) determine how effectiveley parallel hardware and software work together to achieve high performance across a range of problem sizes. In addition, we present the results of compiling this suite using two commercially available parallelizing Fortran compilers, Cray and Convex.