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Titlebook: Languages and Compilers for Parallel Computing; 21th International W José Nelson Amaral Conference proceedings 2008 Springer-Verlag Berlin

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楼主: 毛发
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Efficient Set Sharing Using ZBDDs,the set sharing domain. We show how to synthesize the operations needed in the set sharing transfer functions from basic ZBDD operations. For some of the operations, we devise custom ZBDD algorithms that perform better in practice. We also compare our implementation of the abstract domain with an ef
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Register Bank Assignment for Spatially Partitioned Processors,d, tiled processor with register banks distributed on top of a 4 ×4 grid of ALUs. These results show that the priority banking algorithm implements a number of policies that improve performance, performance is sensitive to bank assignment, and the compiler manages this resource well.
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,Identification of Heap–Carried Data Dependence Via Explicit Store Heap Models,s effectiveness and utility are demonstrated by computing detailed dependence information for two benchmarks (Em3d and BH from the JOlden suite) and using this information to parallelize the benchmarks.
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gluepy: A Simple Distributed Python Programming Framework for Complex Grid Environments,ruct a TCP overlay so as to address connectivity and scalability issues. We have implemented our framework, gluepy as a library for Python. For evaluation, we show on over 900 cores across 9 clusters with complex networks (involving NATs and firewalls) and process managements (involving SSH, torque,
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A Fully Parallel LISP2 Compactor with Preservation of the Sliding Properties,properties. We also prove the correctness of the design. This parallel LISP2 compactor is fully parallel because all of its four phases are parallelized and the workloads are well balanced among the collector threads. The compactor supports fall-back compaction and adjustable boundaries that help de
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A Case Study in Tightly Coupled Multi-paradigm Parallel Programming,. We present a pre-existing adaptive runtime system (ARTS) and show how it can be used to meet these challenges by allowing the simultaneous use of multiple parallel programming paradigms and supporting resource management across all of them. We discuss the implementation of some common paradigms wi
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