Automatic Measurement of Memory Hierarchy Parameters
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Yotov, Kamen; Pingali, Keshav; Stodghill, Paul
On modern computers, the running time of many applications is dominated by the cost of memory operations. To optimize such applications for a given platform, it is necessary to have a detailed knowledge of the memory hierarchy parameters of that platform. In practice, this information is usually poorly documented if at all. Moreover, there is growing interest in self-tuning, autonomic software systems that can optimize themselves for different platforms, and these systems must determine memory hierarchy parameters automatically without human intervention. One solution is to use micro-benchmarks to determine the parameters of the memory hierarchy. In this paper, we argue that existing micro-benchmarks are inadequate, and present novel micro-benchmarks for determining the parameters of all levels of the memory hierarchy, including registers, all caches levels and the translation look-aside buffer. We have implemented these micro-benchmarks into an integrated tool that can be ported with little effort to new platforms. We present experimental results that show that this tool successfully determines memory hierarchy parameters on many current platforms, and compare its accuracy with that of existing tools.
computer science; technical report
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