Four metrics to evaluate heterogeneous multicores

Abstract

Semiconductor device scaling has made single-ISA heterogeneous processors a reality. Heterogeneous processors contain a number of different CPU cores that all implement the same Instruction Set Architecture (ISA). This enables greater flexibility and specialization, as runtime constraints and workload characteristics can influence which core a given workload is run on. A major roadblock to the further development of heterogeneous processors is the lack of appropriate evaluation metrics. Existing metrics can be used to evaluate individual cores, but to evaluate a heterogeneous processor, the cores must be considered as a collective. Without appropriate metrics, it is impossible to establish design goals for processors, and it is difficult to accurately compare two different heterogeneous processors. We present four new metrics to evaluate user-oriented aspects of sets of heterogeneous cores: localized nonuniformity, gap overhead, set overhead, and generality. The metrics consider sets rather than individual cores. We use examples to demonstrate each metric, and show that the metrics can be used to quantify intuitions about heterogeneous cores.