Connor Imes

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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(More)
—The problem of minimizing energy for a performance constraint (e.g., real-time deadline or quality-of-service requirement) has been widely studied, both in theory and in practice. Theoretical models have indicated large potential energy savings, but practical concerns have made these savings hard to realize. Instead, practitioners often rely on heuristic(More)
—Embedded systems are subject to timing and power constraints. To support both, software currently must integrate multiple tools, resulting in additional complexity. We address this problem with a unified, portable framework called Bard which uses control theory to meet the primary constraint and linear programming to optimize the other. We evaluate Bard on(More)
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