Power and Performance Evaluation of Memory-Intensive Applications

Kaiqiang Zhang, Dongyang Ou, Congfeng Jiang, Yeliang Qiu and Longchuan Yan
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Kaiqiang Zhang: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Dongyang Ou: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Congfeng Jiang: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Yeliang Qiu: School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
Longchuan Yan: Information and Communication Corporation, State Grid Corporation of China, Ltd., Beijing 100053, China

Energies, 2021, vol. 14, issue 14, 1-20

Abstract: In terms of power and energy consumption, DRAMs play a key role in a modern server system as well as processors. Although power-aware scheduling is based on the proportion of energy between DRAM and other components, when running memory-intensive applications, the energy consumption of the whole server system will be significantly affected by the non-energy proportion of DRAM. Furthermore, modern servers usually use NUMA architecture to replace the original SMP architecture to increase its memory bandwidth. It is of great significance to study the energy efficiency of these two different memory architectures. Therefore, in order to explore the power consumption characteristics of servers under memory-intensive workload, this paper evaluates the power consumption and performance of memory-intensive applications in different generations of real rack servers. Through analysis, we find that: (1) Workload intensity and concurrent execution threads affects server power consumption, but a fully utilized memory system may not necessarily bring good energy efficiency indicators. (2) Even if the memory system is not fully utilized, the memory capacity of each processor core has a significant impact on application performance and server power consumption. (3) When running memory-intensive applications, memory utilization is not always a good indicator of server power consumption. (4) The reasonable use of the NUMA architecture will improve the memory energy efficiency significantly. The experimental results show that reasonable use of NUMA architecture can improve memory efficiency by 16% compared with SMP architecture, while unreasonable use of NUMA architecture reduces memory efficiency by 13%. The findings we present in this paper provide useful insights and guidance for system designers and data center operators to help them in energy-efficiency-aware job scheduling and energy conservation.

Keywords: energy efficiency; memory system; memory-intensive computing; energy proportionality (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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