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Increasing demand for power-efficient, high-performance computing requires tuning applications and/or the underlying hardware to improve the mapping between workload heterogeneity and computational resources. To assess the potential benefits of hardware tuning, we propose a framework that leverages synergistic interactions between recent advances in (a) sampling, (b) predictive modeling, and (c) optimization heuristics. This framework enables qualitatively new capabilities in analyzing thedoi:10.1145/1353536.1346288 fatcat:jieodfr7urcpjitskiprxq6n7q