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

Abstract

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 ${\text {L}di}{/}{\mathrm {d}t}$ 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.