Abstract
To harness the computational power of massively parallel distributed-memory multicomputers, users must write efficient software. This process is laborious because of the absence of global address space. The programmer must manually distribute computations and data across processors and explicitly manage communication. The Paradigm (PARAllelizing compiler for DIstributed-memory, General-purpose Multicomputers) project at the University of Illinois addresses this problem by developing automatic methods for the efficient parallelization of sequential programs. A unified approach efficiently supports regular and irregular computations using data and functional parallelism.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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