Abstract
Parallel processing is facing a software crisis. The primary reasons for this crisis are the short life span and small installation base of parallel architectures. In this paper, we propose a solution to this problem in the form of an architecture-adaptable programming environment. Our method is different from high-level procedural programming languages in two ways:(1) our system automatically selects the appropriate parallel algorithm to solve the given problem efficiently on the specified architecture (2) by using a divide-and-conquer template as the basic mechanism for achieving parallelism, we considerably simplify the implementation of the system on a new platform. There is a trade-off, however: the loss of generality. From a pragmatic point of view, this is not a major liability since our strategy will be useful in building domain-specific problem solving environments and application-oriented compilers, which are truly machine-independent. We give preliminary results from a case study in which our method is used to adapt the parallel implementations of the conjugate gradient algorithm on a multiprocessor and a workstation network.
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References
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© 1996 Springer Science+Business Media New York
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Kumaran, S., Quinn, M.J. (1996). Machine-Independent Parallel Programming Using the Divide-and-Conquer Paradigm. In: Szymanski, B.K., Sinharoy, B. (eds) Languages, Compilers and Run-Time Systems for Scalable Computers. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2315-4_6
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DOI: https://doi.org/10.1007/978-1-4615-2315-4_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5979-1
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