Power and Performance Evaluation of Memory-Intensive Applications
Power and Performance Evaluation of Memory-Intensive Applications
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DOI：
10.3390/en14144089
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发表时间：
2021-07
期刊：
影响因子：
3.2
通讯作者：
Kaiqiang Zhang;Dongyang Ou;Congfeng Jiang;Yeliang Qiu;Longchuan Yan
中科院分区：
文献类型：
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作者：
Kaiqiang Zhang;Dongyang Ou;Congfeng Jiang;Yeliang Qiu;Longchuan Yan
在功耗和能耗方面，DRAM在现代服务器系统和处理器中发挥着关键作用。虽然功耗感知调度是基于DRAM和其他组件之间的能量比例，但在运行内存密集型应用时，整个服务器系统的能耗会受到DRAM非能量比例的显著影响。此外，现代服务器通常使用NUMA架构来取代原来的SMP架构，以增加其内存带宽。研究这两种不同存储器结构的能量效率具有重要意义。因此，为了探索服务器在内存密集型工作负载下的功耗特性，本文对不同代真实的机架式服务器中内存密集型应用的功耗和性能进行了评估。通过分析，我们发现：（1）内存强度和并发执行线程影响服务器功耗，但充分利用的内存系统不一定带来良好的能效指标。(2)即使内存系统没有得到充分利用，每个处理器内核的内存容量也会对应用程序性能和服务器功耗产生重大影响。(3)在运行内存密集型应用程序时，内存利用率并不总是服务器功耗的良好指标。(4)合理使用NUMA架构将显著提高存储器的能量效率。实验结果表明，与SMP架构相比，合理使用NUMA架构可以提高16%的内存效率，而不合理使用NUMA架构则会降低13%的内存效率。我们在本文中提出的研究结果为系统设计人员和数据中心运营商提供了有用的见解和指导，以帮助他们进行节能意识的作业调度和节能。
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.