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A machine learning approach to multicore resource management produces self-optimizing on-chip hardware agents capable of learning, planning, and continuously adapting to changing workload demands. Machine learning is the study of computer programs and algorithms that learn about their environment and improve automatically with experience.This approach thus contrasts with today's predominant approach of directly specifying at design time how the hardware should accomplish the desired goal. This results in more efficient and flexible management of critical hardware resources at runtime.
Date of Publication: Sept.-Oct. 2009