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Is the owner-computes style of parallelism, captured in a variety of data parallel languages, attractive as a paradigm for designing explicitly parallel codes? This question gives rise to a number of others. Will such use be unwieldy? Will the resulting code run well? What can such an approach offer beyond merely replicating, in a more labor intensive way, the services and coverage of data parallel languages? We investigate these questions via a simple example and a “real world” case study developed using C-Linda, an explicit parallel programming language formed by the merger of C with the Linda 1 coordination language. The results demonstrate owner-computes is an effective design strategy in Linda.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |