Efficient operating system scheduling for performance-asymmetric multi-core architectures

Recent research advocates asymmetric multi-core architectures, where cores in the same processor can have different performance. These architectures support single-threaded performance and multithreaded throughput at lower costs (e.g., die size and power). However, they also pose unique challenges to operating systems, which traditionally assume homogeneous hardware. This paper presents AMPS, an operating system scheduler that efficiently supports both SMP-and NUMA-style performance-asymmetric architectures. AMPS contains three components: asymmetry-aware load balancing, faster-core-first scheduling, and NUMA-aware migration. We have implemented AMPS in Linux kernel 2.6.16 and used CPU clock modulation to emulate performance asymmetry on an SMP and NUMA system. For various workloads, we show that AMPS achieves a median speedup of 1.16 with a maximum of 1.44 over stock Linux on the SMP, and a median of 1.07 with a maximum of 2.61 on the NUMA system. Our results also show that AMPS improves fairness and repeatability of application performance measurements.