  Energy-efficiency has become a major challenge in modern computer systems. To
address this challenge, candidate systems increasingly integrate heterogeneous
cores in order to satisfy diverse computation requirements by selecting cores
with suitable features. In particular, single-ISA heterogeneous multicore
processors such as ARM big.LITTLE have become very attractive since they offer
good opportunities in terms of performance and power consumption trade-off.
While existing works already showed that this feature can improve system
energy-efficiency, further gains are possible by generalizing the principle to
higher levels of heterogeneity. The present paper aims to explore these gains
by considering single-ISA heterogeneous multicore architectures including three
different types of cores. For this purpose, we use the Samsung Exynos Octa 5422
chip as baseline architecture. Then, we model and evaluate Cortex A7, A9, and
A15 cores using the gem5 simulation framework coupled to McPAT for power
estimation. We demonstrate that varying the level of heterogeneity as well as
the different core ratio can lead to up to 2.3x gains in energy efficiency and
up to 1.5x in performance. This study further provides insights on the impact
of workload nature on performance/energy trade-off and draws recommendations
concerning suitable architecture configurations. This contributes in fine to
guide future research towards dynamically reconfigurable HSAs in which some
cores/clusters can be disabled momentarily so as to optimize certain metrics
such as energy efficiency. This is of particular interest when dealing with
quality-tunable algorithms in which accuracy can be then traded for compute
effort, thereby enabling to use only those cores that provide the best
energy-efficiency for the chosen algorithm.
