Abstract
The efficiency of a parallel algorithm with input x on P ≥ 1 processors is defined as \(E(x,P) = \frac{{T(x,1)}}{{PT(x,P)}}\) where T(x, P) denotes the time it takes to perform the computation using P processors and T(x, 1) is the sequential execution time. The efficiency of many parallel algorithms decreases when the number of processors increases and the sequential execution time is fixed; likewise, the efficiency increases when the sequential computing time increases and the number of processors is fixed. The term scalability refers to this change of efficiency (Sahni & Thanvantri, 1996). Intuitively, a parallel algorithm is scalable if it stays efficient when the number of processors and the sequential execution time are both increased.
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Decker, T., Krandick, W. (2001). Isoefficiency and the Parallel Descartes Method. In: Alefeld, G., Rohn, J., Rump, S., Yamamoto, T. (eds) Symbolic Algebraic Methods and Verification Methods. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6280-4_6
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DOI: https://doi.org/10.1007/978-3-7091-6280-4_6
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