Several popular CPU performance metrics are summarized. Hockney’s method for modeling CPU performance as a linear timing equation is discussed and extended to evaluate nonlinear algorithms and their interactions with complex CPU instruction sets. It is argued that instead of determining Hockney’s n1/2 and r∞ of a computer, it is appropriate to determine these values for the combination of the algorithm, compiler, and computer hardware (thus renaming the parameters N1/2 and R∞). The resulting discussion demonstrates how computers and algorithms can be evaluated both separately and as an integrated unit. This method allows users to predict the performance of complex codes using a fairly simple set of measurements. It also provides guidance and rationale for effective program coding styles and design habits.
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Research Article| September 01 1990
Methods for performance evaluation of algorithms and computers
Clifford N. Arnold; Methods for performance evaluation of algorithms and computers. Comput. Phys. 1 September 1990; 4 (5): 514–520. https://doi.org/10.1063/1.168386
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