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ML-powered memory management policies can significantly outperform human-designed heuristics, unlocking performance and efficiency gains previously unattainable in memory subsystems.
By intelligently leveraging application data characteristics and machine learning, microarchitectural designs can overcome memory bottlenecks and achieve substantial performance and energy efficiency gains.