Titlebook: Loyalty to the Monarchy in Late Medieval and Early Modern Britain, c.1400-1688; Matthew Ward,Matthew Hefferan Book 2020 The Editor(s) (if

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Janet Dickinsonads in terms of context-switch overhead and blocking communication. Further, it enables development of blocking data structures that create non-fork-join dependence graphs—which can expose more parallelism, and better supports data-driven computations waiting on results from remote devices.

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Richard Bullockcrotask composed of a sequential loop or a basic block is processed on a processor cluster in the near fine grain by using static scheduling. A macrotask composed of subroutine or a large sequential loop is processed by hierarchically applying macro-dataflow computation inside a processor cluster. P

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pplying the algorithm to parallelizing the Perfect benchmarks, targeted at the KSR-1, and analyze the results. Unlike other approaches, we do not assume an explicit distribution of data to processors. The distribution is inferred from locality constraints and available parallelism. This approach wor

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Edward Legon data distribution, partial computation, delaying updates, and communication. With these extensions to the traditional linear algebra operators, we could produce linear algebra based versions of several problems including single source shortest path that should preform close to custom implementation

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James Harrised for the whole loop)..Our measurements show that if a loop cannot be executed in parallel there is an overhead below 1.6?% compared to the runtime of the original sequential loop. If the loop is parallelizable, we see speedups of up?to a factor of 3.6 on a quad core processor.

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dialect of Java. The middleware supports both distributed memory and shared memory parallelization, and performs a number of I/O optimizations to support efficient processing of disk resident datasets. Our final goal is to start from declarative mining operators, and translate them to data parallel

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