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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