Titlebook: Languages and Compilers for Parallel Computing; 9th International Wo David Sehr,Utpal Banerjee,David Padua Conference proceedings 1997 Spri

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Cross-loop reuse analysis and its application to cache optimizations, accessed in a given loop nest and then accessed again within some subsequent portion of the program, usually another outer loop nest. In contrast to . reuse, which occurs during the execution of a single loop nest, cross-loop reuse is hard to analyze using traditional dependence-based techniques. T

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Locality analysis for distributed shared-memory multiprocessors, growth in the past few years. The focus of this work is on estimation of the memory performance of a loop nest for a given set of computation and data distributions. We assume a distributed shared-memory multiprocessor model. We discuss how to estimate the total number of cache misses (compulsory m

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Data distribution and loop parallelization for shared-memory multiprocessors,ese two actions are not independent and decisions have to be taken in a unified way trying to minimize execution time and data movement costs. The first goal is achieved by parallelizing loops (the main components suitable for parallel execution in scientific codes) and assign work to processors hav

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Data localization using loop aligned decomposition for macro-dataflow processing,ralized shared memory. The data-localization scheme minimizes data transfer overhead for passing shared data among coarse-grain tasks composed of Doall loops and sequential loops by using local memory on each processor effectively. In this scheme, a compiler firstly partitions coarse-grain tasks lik

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Exact versus approximate array region analyses,d under- (or .) approximations of array element sets [25, 33, 21]. In a recent study [13], we proposed to compute . sets whenever possible. But the advantages of this approach were still an open issue which is discussed in this paper..It is first recalled that must array region analyses cannot be de

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Initial results for glacial variable analysis,for value-specific optimization are called candidate variables. They are modified much less frequently than they are referenced. In current systems that use run-time code generation, candidate variables are identified by programmer directives..We describe a novel technique, ., for automatically iden

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Compiler algorithms on if-conversion, speculative predicates assignment and predicated code optimiz which can execute more than one instruction at the same machine cycle to enhance the uniprocessor performance. Since the function units are usually pipelined in such microprocessors, branch misprediction penalty tremendously degrades the CPU performance. In order to reduce the branch misprediction

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