International Conference on Parallel Processing

1 AUTOMATING PARALLELIZATION OF REGULAR COMPUTATIONS FOR DISTRIBUTED-MEMORY MULTICOMPUTERS IN THE PARADIGM COMPILER Ernesto Su, Daniel J. Palermo, and Prithviraj Banerjee Center for Reliable and High-Performance Computing University of Illinois at Urbana-Champaign Urbana, IL 61801, U.S.A. fernesto, palermo, [email protected] Abstract { Distributed-memory multicomputers such as the Intel iPSC/860, the NCUBE/2, the Intel Paragon and the ConnectionMachine CM-5 o er signi cant advantages over shared-memory multiprocessors in terms of cost and scalability. Unfortunately, to extract all the computational power from these machines, users have to parallelize their existing serial programs, which can be an extremely laborious process. One major reason for this di culty is the absence of a single global shared address space. As a result, the programmer has to distribute code and data on processors and manage communication among tasks explicitly. Clearly there is a need for e cient parallelizing compiler support on these machines. The PARADIGM project at the University of Illinois addresses these problems by developing a fully automated means to translate serial programs for e cient execution on distributed-memory multicomputers. In this paper we discuss parallelization of regular computations using symbolic sets as a representation for data accesses and communication.