低熵云的标记架构:理论、实践和教训

IF 2.2 Q3 COMPUTER SCIENCE, CYBERNETICS International Journal of Intelligent Computing and Cybernetics Pub Date : 2022-09-01 DOI:10.34133/2022/9795476
Chuanqi Zhang, Sa Wang, Zihao Yu, Huizhe Wang, Yinan Xu, Luoshan Cai, Dan Tang, Ninghui Sun, Yungang Bao
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引用次数: 0

摘要

资源效率和服务质量(QoS)都是云提供商在过去十年中长期追求的目标。然而,直到今天,几乎没有任何云平台可以完全完美地实现它们。提高资源效率或资源利用率通常会导致不同资源上的托管云应用程序(从底层硬件到软件堆栈)之间出现复杂的资源争用,从而导致意外的性能下降。低熵云提出了一种新的软硬件协同设计技术栈,从下到上整体抑制性能干扰,获得高资源效率和高质量的应用性能。在本文中,我们为低熵云堆栈引入了一种新的计算机体系结构,称为标记冯·诺伊曼体系结构(LvNA),它包含一组标签驱动的控制机制,使芯片上的共享组件和资源能够在竞争硬件资源时区分、隔离和优先考虑用户定义的应用程序请求。借助这些机制的强大功能,LvNA能够保护某些应用程序(如延迟关键型应用程序)的性能,避免无序的资源争用,同时提高资源利用率。我们进一步构建并推出了基于LvNA架构的1.2 GHz 8核RISC-V处理器“北海”。评估结果表明,北海可以将内存带宽争用引起的性能下降从82.8%大幅降低到0.4%。当CPU利用率提高70%以上时,北海可以将Redis的第99次尾部延迟从115 ms降低到18.1 ms。此外,北海还可以实现硬件虚拟化,在没有任何软件管理程序干预的情况下,同时启动两个未修改的虚拟机。
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A Labeled Architecture for Low-Entropy Clouds: Theory, Practice, and Lessons
Resource efficiency and quality of service (QoS) are both long-pursuit goals for cloud providers over the last decade. However, hardly any cloud platform can exactly achieve them perfectly even until today. Improving resource efficiency or resource utilization often could cause complicated resource contention between colocated cloud applications on different resources, spanning from the underlying hardware to the software stack, leading to unexpected performance degradation. The low-entropy cloud proposes a new software-hardware codesigned technology stack to holistically curb performance interference from the bottom up and obtain both high resource efficiency and high quality of application performance. In this paper, we introduce a new computer architecture for the low-entropy cloud stack, called labeled von Neumann architecture (LvNA), which incorporates a set of label-powered control mechanisms to enable shared components and resources on chip to differentiate, isolate, and prioritize user-defined application requests when competing for hardware resource. With the power of these mechanisms, LvNA was able to protect the performance of certain applications, such as latency-critical applications, from disorderly resource contention while improving resource utilization. We further build and tapeout Beihai, a 1.2 GHz 8-core RISC-V processor based on the LvNA architecture. The evaluation results show that Beihai could drastically reduce the performance degradation caused by memory bandwidth contention from 82.8% to 0.4%. When improving the CPU utilization over 70%, Beihai could reduce the 99th tail latency of Redis from 115 ms to 18.1 ms. Furthermore, Beihai can realize hardware virtualization, which boots up two unmodified virtual machines concurrently without the intervention of any software hypervisor.
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CiteScore
6.80
自引率
4.70%
发文量
26
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