MEMS-based Runtime Idle Energy Minimization for Bursty Workloads in Heterogeneous Many-Core Systems

Heterogeneous many-core systems are increasingly being employed in modern embedded applications for high throughput at low energy cost considerations. These applications exhibit bursty workloads that provide with opportunities to minimize system energy. Traditionally, CMOS-based power gating circuitry, consisting of sleep transistors, is used for idle energy reduction in such applications. However, these transistors contribute high leakage current when driving large capacitive loads, making effective energy minimization challenging. In this paper, we propose a novel MEMS-based runtime energy minimization approach. Core to our approach is an integrated sleep mode management based on the performance-energy states and bursty workloads indicated by the performance counters. For effective energy minimization we use a systematic optimization of the controller design parameters by adopting finite element analysis (FEA) in multiphysics COMSOL tool. A number of PARSEC benchmark applications are used as case studies of bursty workloads, including CPU-and memory-intensive ones. These applications are exercised on an Exynos 5422 heterogeneous many-core platform showing up to 50% energy savings when compared with ondemand governor. Furthermore, we provide all extensive trade-off analysis to demonstrate the comparative advantages of MEMS-based controller, including zero-leakage current and non-invasive implementations suitable for commercial off-the-shelf systems.