The time and energy efficiency of modern multicore systems

Abstract

With the increasing adoption of homogeneous and heterogeneous shared-memory multicore systems, we aim to improve the understanding of their time and energy performance by extending the classic speedup laws proposed by Amdahl and Gustafson. We derive speedup equations for heterogeneous systems and introduce energy savings models for both homogeneous and heterogeneous multicores. These models use two key parameters, (i) the active power fraction (APF) of a core which represents the ratio between the core’s average active power and the power of the idle system, and (ii) the inter-core speedup (ICS) representing the difference in speed among different types of cores in a heterogeneous system. Using both modeling and measurements, we show that energy savings are achievable, but limited by the APF on systems with large core counts and by both the APF and workload’s sequential fraction on systems with low core counts. Our models are validated against measurements on modern multicore systems including two homogeneous servers with 48 cores which represent both traditional brawny x86/64 and emerging wimpy ARM nodes, and two heterogeneous wimpy systems with ARM big.LITTLE and NVIDIA Denver cores, respectively.