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Energy Optimization of Multiprocessor Systems on Chip by Voltage Selection

机译:通过电压选择优化片上多处理器系统的能量

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Dynamic voltage selection and adaptive body biasing have been shown to reduce dynamic and leakage power consumption effectively. In this paper, we optimally solve the combined supply voltage and body bias selection problem for multiprocessor systems with imposed time constraints, explicitly taking into account the transition overheads implied by changing voltage levels. Both energy and time overheads are considered. The voltage selection technique achieves energy efficiency by simultaneously scaling the supply and body bias voltages in the case of processors and buses with repeaters, while energy efficiency on fat wires is achieved through dynamic voltage swing scaling. We investigate the continuous voltage selection as well as its discrete counterpart, and we prove strong NP-hardness in the discrete case. Furthermore, the continuous voltage selection problem is solved using nonlinear programming with polynomial time complexity, while for the discrete problem, we use mixed integer linear programming and a polynomial time heuristic. We propose an approach that combines voltage selection and processor shutdown in order to optimize the total energy
机译:动态电压选择和自适应主体偏置已被证明可以有效降低动态和泄漏功耗。在本文中,我们明确地考虑了电压电平变化所隐含的过渡开销,从而为带有时间限制的多处理器系统最优地解决了组合电源电压和本体偏置选择问题。同时考虑了能源和时间开销。在处理器和带有中继器的总线的情况下,电压选择技术通过同时缩放电源电压和车身偏置电压来实现能源效率,而粗电线上的能量效率通过动态电压摆幅缩放实现。我们研究了连续电压选择及其不连续的选择,并证明了在不连续情况下的强NP硬度。此外,使用具有多项式时间复杂度的非线性编程来解决连续电压选择问题,而对于离散问题,我们使用混合整数线性编程和多项式时间启发式方法。我们提出了一种将电压选择和处理器关闭相结合的方法,以优化总能量

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