METRIC: tracking down inefficiencies in the memory hierarchy via binary rewriting

We present METRIC, an environment for determining memory inefficiencies by examining data traces. METRIC is designed to alter the performance behavior of applications that are mostly constrained by their latency to resolve memory references. We make four primary contributions. First, we present meth...

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Bibliographic Details
Main Authors: Marathe, J., Mueller, F., Mohan, T., de Supinski, B.R., McKee, S.A., Yoo, A.
Format: Conference Proceeding
Language:English
Subjects:
Computational modeling
Computer architecture
Contracts
Delay
Instruments
Laboratories
Large-scale systems
Libraries
Manipulator dynamics
Subcontracting
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Summary:We present METRIC, an environment for determining memory inefficiencies by examining data traces. METRIC is designed to alter the performance behavior of applications that are mostly constrained by their latency to resolve memory references. We make four primary contributions. First, we present methods to extract partial data traces from running applications by observing their memory behavior via dynamic binary rewriting. Second, we present a methodology to represent partial data traces in constant space for regular references through a novel technique for online compression of reference streams. Third, we employ offline cache simulation to derive indications about memory performance bottlenecks from partial data traces. By exploiting summarized memory metrics, by-reference metrics as well as cache evictor information, we can pin-point the sources of performance problems. Fourth, we demonstrate the ability to derive opportunities for optimizations and assess their benefits in several experiments resulting in up to 40% lower miss ratios.
DOI:10.1109/CGO.2003.1191553