Embarrassingly parallel problems are characterised by a very small amount of information to be exchanged among the parts they are split in, during their parallel execution. As a consequence they do not require sophisticated, low-latency, high-bandwidth interconnection networks but can be efficiently computed in parallel by exploiting commodity hardware. Basically, this means cheap clusters, networks of workstations and desktops, and Computational Clouds. This computational model can be exploited to compute a quite large range of problems. This paper describes Sci-φ, an almost complete redesign of a previous tool of ours aimed at developing task parallel applications based on Java and Jini that were shown to be an effective and efficient solution in environments like clusters and networks of workstations and desktops.
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| http://dx.doi.org/10.1155/2014/526953 | DOI Listing |
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