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Abstract. We present a new benchmark suite for parallel computers. SPEComp targets mid-size parallel servers. It includes a number of science/engineering and data processing applications. Parallelism is expressed in the OpenMP API. The suite includes two data sets, Medium and Large, of approximately 1.6 and 4 GB in size. Our overview also describes the organization developing SPEComp, issues in creating OpenMP parallel benchmarks, the benchmarking methodology underlying SPEComp, and basic performance characteristics.

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Most current data dependence tests cannot handle loop bounds or array subscripts that are symbolic, nonlinear expressions (e.g. A(n i+j), where 0 j n). In this paper, we describe a dependence t e s t , c alled the range test, that can handle such expressions. Brie y, the range test proves independence by determining whether certain symbolic inequalities hold for a permutation of the loop nest. Powerful symbolic analyses and constraint propagation techniques were developed t o p r ove such inequalities. T h e r ange test has been implemented in Polaris, a parallelizing compiler being developed at the University of Illinois.

The elimination of induction variables and the parallelization of reductions in FORTRAN programs have been shown to be integral to performance improvement on parallel computers 7, 8].As part of the Polaris project 5], compiler passes that recognize these idioms have been implemented a n d e v aluated. Developing these techniques to the point necessary to achieve signi cant speedups on real applications has prompted solutions to problems that have not been addressed in previous reports on idiom recognition techniques. These include analysis techniques capable of disproving zero-trip loops, symbolic handling facilities to compute closed forms of recurrences, and interfaces to other compilation passes such as the data-dependence test. In comparison, the recognition phase of solving induction variables, which has received most attention so far, has in fact turned out to be relatively straightforward. This paper provides an overview of techniques described in more detail in 12].

Abstract. Cetus is a compiler infrastructure for the source-to-source transformation of programs. We created Cetus out of the need for a compiler research environment that facilitates the development of interprocedural analysis and parallelization techniques for C, C++, and Java programs. We will describe our rationale for creating a new compiler infrastructure and give an overview of the Cetus architecture. The design is intended to be extensible for multiple languages and will become more flexible as we incorporate feedback from any difficulties we encounter introducing other languages. We will characterize Cetus' runtime behavior of parsing and IR generation in terms of execution time, memory usage, and parallel speedup of parsing, as well as motivate its usefulness through examples of projects that use Cetus. We will then compare these results with those of the Polaris Fortran translator.