No abstract available.

In this paper we investigate a unique problem associated with fusing loops within a High Performance Fortran (HPF) program. In particular, we discuss the issue of performing loop fusion in an HPF compiler when compiling Fortran90 array assignment statements for execution on a distributedmemory machine. During compilation of an HPF program, Fortran90 array assignment statements must be scalarized into loop nests. We show how a certain class of these loop nests, when fused, can cause problems for the compiler's distributed-memory code generator. We then present an algorithm which not only prevents the fusion of these loops, but also increases the amount of useful fusion that can be performed. 1 Introduction High-Performance Fortran (HPF)[12], an extension of Fortran90, has attracted considerable attention as a promising language for writing portable parallel programs. HPF offers a simple programming model shielding programmers from the intricacies of concurrent programming and managing ...

For many Fortran90 and HPF programs performing dense matrix computations, the main computational portion of the program belongs to a class of kernels known as stencils. Stencil computations are commonly used in solving partial differential equations, image processing, and geometric modeling. The efficient handling of such stencils is critical for achieving high performance on distributed-memory machines. Compiling stencils into efficient code is viewed as so important that some companies have built special-purpose compilers for handling them and others have added stencil-recognizers to existing compilers.In this paper we present a general compilation strategy for stencils written using Fortran90 array constructs. Our strategy is capable of optimizing single or multi-statement stencils and is applicable to stencils specified with shift intrinsics or with array-syntax all equally well. The strategy eliminates the need for pattern-recognition algorithms by orchestrating a set of optimizations that address the overhead of both intraprocessor and interprocessor data movement that results from the translation of Fortran90 array constructs. Our experimental results show that code produced by this strategy beats or matches the best code produced by the special-purpose compilers or pattern-recognition schemes that are known to us. In addition, our strategy produces highly optimized code in situations where the others fail, producing several orders of magnitude performance improvement, and thus provides a stencil compilation strategy that is more robust than its predecessors.

The ParaScope Editor is an interactive parallel programming tool that assists knowledgeable users in developing scientific Fortran programs. It displays the results of sophisticated program analyses, provides a set of powerful interactive transformations, and supports program editing. This paper summarizes experiences of scientific programmers and tool designers using the ParaScope Editor. We evaluate existing features and describe enhancements in three key areas: user interface, analysis, and transformation. many existing features prove crucial to successful program parallelization. They include interprocedural array side-effect analysis and program and dependence view filtering. Desirable functionality includes improved program navigation based on performance estimation, incorporating user assertions in analysis and more guidance in selecting transformations. These results offer insights for the authors of a variety of programming tools and parallelizing compilers.