Definition
Here it is asked which applications should run in parallel and correspondingly which areas of computational science will benefit from parallelism. In studying this it will be discovered which applications benefit from particular hardware and software choices. A driving principle is that in parallel programming, one must map problems into software and then into hardware. The architecture differences in source and target of these maps will affect the efficiency and ease of parallelism.
Discussion
Introduction
I have an application – can and should it be implemented on a parallel architecture and if so, how should this be done and what are appropriate target hardware architectures, what is known about clever algorithms and what are recommended software technologies? Fox introduced in [1] a general approach to this question by considering problems and the computer infrastructure on which they are executed as complex...
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Fox, G. (2011). Computational Sciences. In: Padua, D. (eds) Encyclopedia of Parallel Computing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09766-4_274
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DOI: https://doi.org/10.1007/978-0-387-09766-4_274
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