Power, energy, and performance analysis of single- and multi-threaded applications in the ARM ThunderX2

• Published in: Journal of parallel and distributed computing Vol. 204; p. 105118
• Main Authors: Calero, Ibai, Petit, Salvador, Gómez, María E., Sahuquillo, Julio
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.10.2025
• Subjects: Characterization; Energy efficiency; Inter-application interference; Multi-core processors; Power consumption; Characterization; Energy efficiency; Power consumption; Performance; Inter-application interference; Multi-core processors
• ISSN: 0743-7315
• DOI: 10.1016/j.jpdc.2025.105118

Energy efficiency has been a major concern in data centers, and the problem is exacerbated as its size continues to rise. However, the lack of tools to measure and handle this energy at a fine granularity (e.g., processor core or last-level cache) has translated into slow research advances in this topic. Understanding where (i.e., which components) and when (the point in time) energy consumption translates into minor performance improvements is of paramount importance to design any energy-aware scheduler. This paper characterizes the relationship between energy consumption and performance in a 28-core ARM ThunderX2 processor for both single-threaded and multi-threaded applications. This paper shows that single-threaded applications with high CPU activity maintain their performance in spite of the inter-application interference at shared resources, but this comes at the expense of higher power consumption. Conversely, applications that heavily utilize the L3 cache and memory consume less power but suffer significant performance degradation as interference levels rise. In contrast, multi-threaded applications show two distinct behaviors. On the one hand, some of them experience significant performance gains when they execute in a higher number of cores with more threads, which outweighs the increase in power consumption, leading to high energy efficiency. •Energy efficiency is of extreme importance in modern data centers.•Lack of fine-grained energy counters hinders improvements in energy efficiency.•Use of performance counters to estimate power in various domains of a manycore CPU.•Characterization of single-threaded applications and inter-application interference.•Analysis of multi-threaded applications when increasing its number of threads.