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Unformatted text preview: when running on a lightly loaded machine. We exploit these properties to get reliable estimates of true run times. As our object to measure, we used a procedure that repeatedly writes values to an array of 2,048 integers and then reads them back, similar to the code for clear cache. By setting the number of repetitions Ö , we could create computations requiring a range of times. We first determined the expected run time of this procedure as a function of Ö , denoted Ì ´Ö µ, by timing it for Ö ranging from 1 to 10 (giving times ranging from 0.09 to 0.9 milliseconds), and performing a least squares fit to find a formula of the form Ì ´Ö µ ÑÖ · . By using small values of Ö , performing 100 measurements for each value of Ö , and running on a lightly loaded system we were able to get a very accurate characterization of Ì ´Ö µ. Our least squares analysis indicated that the formula Ì ´Ö µ ¾ ¿ Ö ·½ (in units of clock cycles) fits this data with a maximum error less than 0.04%. This gave us confidence...
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This note was uploaded on 09/02/2010 for the course ELECTRICAL 360 taught by Professor Schultz during the Spring '10 term at BYU.

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