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Embedded real-time systems must meet timing constraints while minimizing energy consumption. To this end, many energy optimizations are introduced for specific platforms or specific applications. These solutions are not portable, however, and when the application or the platform change, these solutions must be redesigned. Portable techniques are hard to(More)
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)
As energy consumption becomes a first class concern for computing systems, there is an increasing need for application-level access to runtime power/energy measurements. To support this need, a growing number of power and energy monitors are being developed, each with their own interfaces. In fact, the approaches are extremely diverse, and porting(More)
Many modern software applications have performance requirements, like mobile and embedded systems that must keep up with sensor data, or web services that must return results to users within an acceptable latency bound. For such applications, the goal is not to run as fast as possible, but to meet their performance requirements with minimal resource usage,(More)
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)
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