Abstract

this paper, we describe techniques developed in the Rice dHPF compiler to address key code generation challenges that arise in achieving high performance for regular applications on message-passing systems. We focus on techniques required to implement advanced optimizations and to achieve consistently high performance with existing optimizations. Many of the core communication analysis and code generation algorithms in dHPF are expressed in terms of abstract equations manipulating integer sets. This approach enables general and yet simple implementations of sophisticated optimizations, making it more practical to include a comprehensive set of optimizations in data-parallel compilers. It also enables the compiler to support much more aggressive computation partitioning algorithms than in previous compilers. We therefore believe this approach can provide higher and more consistent levels of performance than are available today. 1. Introduction

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