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UW-Madison
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A dynamic selection approach among microarchitectural policies can recover over 70% of performance potential without executing inactive policies.
Machine-learning predictors can mislead design decisions, with over 22% of configurations showing unexpected performance reversals that traditional simulation still captures best.
