ML predictors rank processor configurations well in aggregate but fall below chance on counter-intuitive reversals and barely beat a no-feature baseline for closely matched policies.
Construction and use of linear regression models for processor performance analysis,
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On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies
ML predictors rank processor configurations well in aggregate but fall below chance on counter-intuitive reversals and barely beat a no-feature baseline for closely matched policies.