Minimizing energy under performance constraints on embedded platforms: resource allocation heuristics for homogeneous and single-ISA heterogeneous multi-cores

This paper explores the problem of energy optimization in embedded platforms. Specifically, it studies resource allocation strategies for meeting performance constraints with minimal energy consumption. We present a comparison of solutions for both homogeneous and single-ISA heterogeneous multi-core embedded systems. We demonstrate that different hardware platforms have fundamentally different performance/energy tradeoff spaces. As a result, minimizing energy on these platforms requires substantially different resource allocation strategies. Our investigations reveal that one class of systems requires a race-to-idle heuristic to achieve optimal energy consumption, while another requires a never-idle heuristic to achieve the same. The differences are dramatic: choosing the wrong strategy can increase energy consumption by over 2× compared to optimal.

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