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Overlapping communication with computation is a well-known approach to improving performance. Previous research has focused on optimizations performed by the programmer. This paper presents a compiler algorithm that automatically determines the appropriate loop indices of a given nested loop and applies loop interchange and tiling in order to overlap communication with computation. The algorithm avoids generating redundant communication by providing a framework for combining information on data dependence, communication, and reuse. It also describes a method of generating messages to exchange data between processors for tiled loops on distributed memory machines. The algorithm has been implemented in our High Performance Fortran (HPF) compiler, and experimental results have shown its effectiveness on distributed memory machines, such as the RISC System/6000 Scalable POWERparallel System. This paper also discusses the architectural problems of efficient optimization. [ABSTRACT FROM AUTHOR]

This paper considers the role of run-time diagnostic checking in enforcing the rules of the Pascal programming language. Run- time diagnostic checks must be both complete (covering all language requirements) and efficient. Further, such checks should be implemented so that the cost of enforcing the correct use of a given construct is borne by users of that construct. This paper describes simple and efficient mechanisms currently in use with a diagnostic Pascal compiler that monitor the run-time behavior of such sensitive Pascal constructs as pointers, variant records, reference (i.e., vat) parameters, and with statements. The use of these mechanisms with related constructs in other languages is considered. Language modifications that simplify run-time checking are also noted. [ABSTRACT FROM AUTHOR]

This article introduces the themes of the papers featured in the April 2000 special issue of the "International Journal of Parallel Programming." The first paper describes a loop transformation algorithm. The second paper proposes a new way to develop concurrent programs, called hypersequential programming. The third paper introduces a workstation cluster implementing a distributed shared-memory mechanism. Lastly, the fourth paper discusses issues of multilevel parallelization and how they affect design of parallelizing compilers.