Batt_Model_SSST_pap - Energy Source Lifetime Optimization...

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Energy Source Lifetime Optimization for a Digital System through Power Management Manish Kulkarni and Vishwani D. Agrawal Department of Electrical and Computer Engineering Auburn University Auburn, AL 36849, Abstract —We examine the energy consumption of a digital circuit with voltage scaling and observe its impact on the energy efficiency of the battery. We study the system with a power source under throughput constraints and we propose a method to find a right size of battery to satisfy given system requirements. For systems with limit on battery weight or volume, we suggest a right circuit voltage operating point. Maximizing battery lifetime, expressed in terms of clock cycles, depends upon a proper choice of the supply voltage and the corresponding clock frequency that the circuit would support. Analysis of various battries shows that when no system performance requirement is specified, the optimum operating supply can be in the subthreshold range. I. INTRODUCTION Every processor chip has a physical limit on power dissi- pation it can support. For systems that use these processors, performance and power become opposing requirements. Mod- ern computing systems, therefore, have built-in power control schemes. For example, thermal sensors on a processor chip may trigger a slowdown of the processor clock [2]. There are various factors which force designers to consider low power as one of the main goals. More and more transistors are being packed into a single core, and more cores per chip, as the scale of integration improves. This leads to steady growth of operating frequency and processing capacity per chip, resulting in increased power dissipation. Since present generation devices are at a safe distance from reaching their fundamental physical limits, the evolution would continue for a while. Another factor that fuels need for low power chips is the increased market demand for Mobile Internet Devices (MIDs) powered by batteries. Batteries have not experienced a rapid density growth. The specific weight (stored energy per unit weight) of batteries barely doubles in several years [25] as shown in Figure 1. Also, further increase in battery specific weight will create concerns about their safety as the energy density will approach that of explosive chemicals. So battery technology is not going to solve the power problem in near future. For mobile systems, energy consumption and the rate of consumption (power) are directly related to the battery capacity. Higher discharge rate reduces the capacity, requiring bulkier batteries with higher current rating [4] or more frequent recharging. Thus, it is important to control the power consumption. For MIDs, consideration of a suitable metric is also important since the ultimate aim is to achieve maximum battery lifetime or more operations per recharge. Traditional metrics like power and energy are not sufficient
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This note was uploaded on 09/17/2011 for the course ELEC 6970 taught by Professor Staff during the Spring '08 term at Auburn University.

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Batt_Model_SSST_pap - Energy Source Lifetime Optimization...

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