Deep Reinforcement Learning for System-on-Chip: Myths and Realities
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DOI: 10.1109/access.2022.3203401
Abstract: Neural schedulers based on deep reinforcement learning (DRL) have shown considerable potential for solving real-world resource allocation problems, as they have demonstrated significant performance gain in the domain of cluster computing. In this paper, we… read more here.
Keywords: reinforcement learning; deep reinforcement; neural schedulers; system chip ... See more keywords