A Comparison of Counting and Sampling Modes of Using Performance Monitoring Hardware
ICCS '02 Proceedings of the International Conference on Computational Science-Part II
SMARTS: accelerating microarchitecture simulation via rigorous statistical sampling
Proceedings of the 30th annual international symposium on Computer architecture
Online performance analysis by statistical sampling of microprocessor performance counters
Proceedings of the 19th annual international conference on Supercomputing
A new metric for measuring metamodels quality-of-fit for deterministic simulations
Proceedings of the 38th conference on Winter simulation
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In sampling based hotspot detection, performance engineers sample the running program periodically and record the Instruction Pointer (IP) addresses at the sampling. Empirically, frequently sampled IP addresses are regarded as the hotspot of the program. The question of how well the sampled hotspot IP addresses match the real hotspot of the program is seldom studied by the researchers. In this paper, we use instrumentation tool to count how many times the sampled hotspot IP addresses are executed, and compare the real execution result with the sampled one to see how well they match. We define the normalized root mean square error, the sample coverage and the order deviation to evaluate the difference between the real execution and the sampled results. Experiment on the SPEC CPU 2006 benchmarks with various sampling periods is performed to verify the proposed evaluation measurements. Intuitively, the sampling accuracy decreases with the increase of sampling period. The experimental results reveal that the order deviation reflects the intuitive relation between the sampling accuracy and the sampling period better than the normalized root mean square error and the sample coverage.