ESHMP: A Stall-Time-Based Scheduling for Performance Heterogeneous Multicore Systems

Recent research advocates performance heterogeneous multicore processors, where cores in the same processor have same instruction set architecture (ISA) but often different performance characteristics. These architectures are able to deliver higher performance per watt and area for programs with diverse architectural requirements than comparable homogeneous ones. However, such power and area efficiencies of performance heterogeneous multicore systems can only be accomplished when thread-to-core assignment is made according to the characteristics of both the workload and the core. In this paper, we propose a new metric, ASTPI (Average Stall Time Per Instruction), to measure the properties of threads. We design, implement and evaluate a new online monitoring approach called ESHMP, which is based on the metric. Our evaluation in the Linux 2.6.21 operating system shows that ESHMP delivers scalability while adapting to a wide variety of applications.