This paper uses fractals to model the clustering of cache misses. The clustering of cache misses can be quantified by a single number analog to a fractional dimension, and we are intrigued by the possibility that this number can be used as a measure of software complexity. The essential intuition is that cache misses are a direct reflection of changes in locality of reference, and that complex software requires more frequent (and larger) changes in this locality than simple software. The cluster dimension provides a measure (and perhaps the basis for a model) of the intrinsic differences between workloads. In this paper, we focus on cache miss activity as a discriminate between interactive and batch environments.
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