State of the art in compiling HPF

Coelho, Fabien; Germain, Cécile; Pazat, Jean-Louis

doi:10.1007/3-540-61736-1_45

Cited by 10 publications

(2 citation statements)

References 23 publications

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“…Two strategies are possible for the compilation of a forall loop, according to the way the owner computes rule is applied [6]. The first one, run time resolution, evaluates at run time the owner computes rule.…”

Section: Figure 1 Code Generated By the Run-time Resolutionmentioning

confidence: 99%

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Evaluation of a virtual shared memory machine by the compilation of data parallel loops

Baiardi

Guerri

Mori

et al.

Proceedings 8th Euromicro Workshop on Parallel and Distributed Processing

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We introduce DVSA, distributed virtual shared areas, a virtual machine supporting the sharing of information on distributed memory architectures. The shared memory is structured as a set of areas where the size of each area may be chosen in an architecture dependent range. DVSA supports the sharing of areas rather than of variables because the exchange of chunks of data may result in better performances on distributed memory architectures offering little or no hardware support to information sharing. DVSA does not implement replication or prefetching strategies under the assumption that these strategies should be implemented by application specific virtual machines. The definition of these machines may often be driven by the compilation of the adopted programming languages.To validate the assumption, at first we consider the implementation of data parallel loops and show that a set of static analyses based on the closed forms approach makes it possible to define compiler driven caching and prefetching strategies. These strategies fully exploit the operations offered by the DVSA machine and they noticeably reduce the time to access shared information. The optimizations strategies that can be exploited by the compiler includes the merging of accesses to avoid multiple access to the same area, the prefetching of areas and the reduction of the overhead due to barrier synchronization. Preliminary performance figures are discussed.

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Section: Figure 1 Code Generated By the Run-time Resolutionmentioning

confidence: 99%

“…The most relevant ones [6] are those based on the computation of closed forms, on the definition of automata and on linear integer programming techniques.…”

Section: Code Generation: Static Resolutionmentioning

confidence: 99%