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Titlebook: Languages and Compilers for Parallel Computing; 5th International Wo Utpal Banerjee,David Gelernter,David Padua Conference proceedings 1993

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Handling distributed data in Vienna Fortran procedures, using global data references. Thus, the user has the advantages of a shared memory programming paradigm while explicitly controlling the data distribution. In this paper, we specify the mechanisms in Vienna Fortran that control the transfer of distributed arrays to procedures, and illustrate a number of applications.
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0302-9743 aca (1988). As in previous years, a reasonablecross-section ofsome of the best work in the field ispresented. The volume contains 35 papers, mostly by authorsworking in the U.S. or Canada but also by authors fromAustria, Denmark, Israel, Italy, Japan and the U.K.978-3-540-57502-3978-3-540-48201-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Supporting SPMD execution for dynamic data structures,ted data. Second, we explain how to introduce parallelism into the model using a technique based on futures and lazy task creation[21]. Third, we present the compiler analyses and parallelization techniques that are required to exploit the proposed mechanism.
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0302-9743 mputing, held at Yale University,August 1992. The previous workshops inthis series were heldin Santa Clara (1991), Irvine (1990), Urbana (1989),andIthaca (1988). As in previous years, a reasonablecross-section ofsome of the best work in the field ispresented. The volume contains 35 papers, mostly by
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Compiler optimizations for massively parallel machines: Transformations on iterative spatial loops,gonal systems by Gaussian Elimination, the performance of the optimized native code is two orders of magnitude better than the CM-FORTRAN compiler and approaching that of the hand-written Connection Machine Scientific Library (CMSSL) routine.
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Collective loop fusion for array contraction,for array contraction [13]. This paper extends this work by including the loop fusion optimization. The fusion method discussed in this paper uses the maxflow-mincut algorithm to do loop clustering. Our collective loop fusion algorithm is efficient, and we demonstrate its usefulness for array contraction with a simple example.
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