It is widely acknowledged in high-performance computing circles that parallel input/output needs substantial improvement in order to make scalable computers truly usable. We present a data storage model that allows processors independent access to their own data and a corresponding compilation strategy that integrates data-parallel computation with data distribution for out-of-core problems. Our results compare several communication methods and I/O optimizations using two out-of-core problems, Jacobi iteration and LU factorization.

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.