University of Cambridge researchers published "Machine Learning for Energy-Performance-aware Scheduling."
Abstract
"In the post-Dennard era, optimizing embedded systems requires navigating complex trade-offs between energy efficiency and latency. Traditional heuristic tuning is often inefficient in such high-dimensional, non-smooth landscapes. In this work, we propose a Bayesian Optimizatio...
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