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To model cache behavior in a multiprogramming environment, it is necessary to know the number of distinct lines referenced in an execution interval. The stack growth function (SGF) relates the mean number of references (or instructions) to the number of distinct lines referenced; it can be viewed as the inverse function of the mean working set size. A fast, one-pass algorithm to compute the SGF
cache behavior; multiprogramming environment; execution interval; stack growth function; SGF; one-pass algorithm; inverse exponential model; buffer storage; multiprogramming; performance evaluation.

M. MacDougall and M. Kobayashi, "The Stack Growth Function: Cache Line Reference Models," in IEEE Transactions on Computers, vol. 38, no. , pp. 798-805, 1989.
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