The Paradigm compiler for distributed-memory multicomputers

P. Banerjee, J.A. Chandy, M. Gupta, E.W. Hodges, J.G. Holm, A. Lain, D.J. Palermo, S. Ramaswamy, E. Su
1995 Computer  
A flexible compiler framework for distributed-memory multicomputers automatically parallelizes sequential programs. A unified approach efficiently supports regular and irregular computations using data and functional parallelism. M assively parallel distributed-memory multicomputers can achieve the high performance levels required to solve the Grand Challenge computational science problems (a class of computational applications, identified by the 1992 US Presidential Initiative in
more » ... ce Computing and Communications, that would require a significant increase in computing power). Multicomputers such as the Intel Paragon, the IBM SP-l/SP-2 (Scalable PowerParallel 1 and 2) and the Thinking Machines CM-5 (Connection Machine 5) offer significant cost and scalability advantages over shared-memory multiprocessors. However, to harness these machines' computational power, 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 efficient parallelization of sequential programs.
doi:10.1109/2.467577 fatcat:ghmtervcfzehzlelvf2ealwgyu