A study of DVFS methodologies for multicore systems with islanding feature

Abstract

Abstract High performance computing centers need to keep up with the growing applications of varying computational characteristics. High computation rates result in consuming vast amounts of energy with increasing electricity costs. To fulfill computational demands with reasonable energy consumption cost, dynamic voltage and frequency scaling (DVFS) technique is used for scaling voltage/frequency (V/F) levels of cores based on their time-varying workloads during application runtime. This book chapter investigates improving multicore system energy efficiency with DVFS, where optimization goal is to minimize application execution time while maintaining the energy consumption below a user-defined energy budget and vice versa. This optimization goal is achieved by performing DVFS at fine-grain level, which adjusts individual cores V/F levels, and at coarse-grain level, which divides the cores into multiple voltage/frequency islands (VFIs), where all the cores in each VFI share a common V/F level. Despite being very energy-efficient, the fine-grain VFIs have high implementation overheads. The coarse-grain VFIs provide acceptable energy efficiency with lower overheads. The fine-grain DVFS establishes energy efficiency optimality used for evaluating the coarse-grain VFIs performance. Factors considered for improving the coarse-grain VFIs energy efficiency include scheduling tasks among VFIs, clustering cores with similar workloads across application execution intervals, and fixing the VFIs V/F levels for the entire application runtime or adjusting them per application execution interval. The fine- and coarse-grain VFIs energy efficiency performances, optimized at compile-time, are evaluated on multiple applications that have varying computational characteristics. This book chapter also evaluates these optimization methodologies scalabilities for systems with different number of cores.