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Noise-Aware DVFS for Efficient Transitions on Battery-Powered IoT Devices

机译:用于电池供电的IOT设备上有效转换的噪声感知DVF

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Low power system-on-chips (SoCs) are now at the heart of Internet-of-Things (IoT) devices, which are well-known for their bursty workloads and limited energy storage-usually in the form of tiny batteries. To ensure battery lifetime, dynamic voltage frequency scaling (DVFS) has become an essential technique in such SoC chips. With continuously decreasing supply level, noise margins in these devices are already being squeezed. During DVFS transition, large current that accompanies the clock speed transition runs into or out of clock networks in a few clock cycles, induces large Ldi/dt noise, thereby stressing the power delivery system (PDS). Due to the limited area and cost target, adding additional decoupling capacitance to mitigate such noise is usually challenging. A common approach is to gradually introduce/remove the additional clock cycles to increase/decrease the clock frequency in steps, also known as, clock skipping. However, such a technique may increase DVFS transition time, and still cannot guarantee minimal noise. In this paper, we propose a new noise-aware DVFS sequence optimization technique by formulating a mixed 0/1 programming to resolve the problems of clock skipping sequence optimization. Moreover, the method is also extended to schedule extensive wake-up activities on different clock domains for the same purpose. The experiments show that the optimized sequence is able to significantly mitigate noise within the desired transition time, thereby saving both power and energy.
机译:低功耗系统上芯片(SOC)现在处于互联网(IOT)设备的核心,这对于他们的爆发工作负载和能量存储有限 - 通常以微小的电池的形式而闻名。为确保电池寿命,动态电压频率缩放(DVFS)已成为此类SoC芯片中的基本技术。随着供应水平持续降低,这些设备中的噪声边距已经被挤压。在DVFS过渡期间,伴随时钟速度转换的大电流在几个时钟周期中运行到时钟网络中,引起大的LDI / DT噪声,从而强调电力输送系统(PDS)。由于区域有限和成本目标,增加额外的去耦电容以减轻这种噪音通常具有挑战性。一种常见的方法是逐步引入/去除额外的时钟周期以增加/减少步骤中的时钟频率,也称为时钟跳跃。然而,这种技术可以增加DVFS过渡时间,并且仍无法保证最小的噪声。在本文中,我们通过制定混合的0/1编程来解决新的噪声感知DVFS序列优化技术,以解决时钟跳过序列优化问题。此外,该方法还扩展以在不同的时钟域中安排广泛的唤醒活动以获得相同的目的。实验表明,优化的序列能够显着降低所需转变时间内的噪声,从而节省了功率和能量。

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