Efficient Power Management for Heterogeneous Multi-Core Architectures

Abstract

Relentless Complementary Metal-Oxide Semiconductor (CMOS) scaling at deep sub-micron level has resulted in increased power density in microprocessor, which forced the computing systems to move in the direction of parallel architectures with homogeneous multi-cores. However, the emergence of dynamic and diverse workloads combined with the failure of Dennard Scaling facilitated the growth of heterogeneous multi-cores. The presence of heterogeneity enables better match between application demand and computation capabilities leading to substantially improved performance and energy-efficiency. In spite of significant benefits in terms of both performance and energy consumption, the heterogeneous multicore systems introduce many of design and scheduling challenges. In this thesis, we address various challenges involved in designing heterogeneous multi-cores.