Achieving middleware execution efficiency: hardware-assisted garbage collection operations

Achieving middleware execution efficiency: hardware-assisted garbage collection operations
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实现中间件执行效率:硬件辅助垃圾收集操作

DOI:
10.1007/s11227-010-0493-0
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发表时间:
2012-03
影响因子:
3.3
通讯作者:
Gaudiot, Jean-Luc
Gaudiot, Jean-Luc
中科院分区:
计算机科学4区
文献类型:
--
作者:
Tang, Jie;Liu, Shaoshan;Gu, Zhimin;Li, Xiao-Feng;Gaudiot, Jean-Luc

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虽然虚拟化技术给云计算环境带来了很多好处,但随着虚拟机提供的功能越来越多,中间件层变得臃肿,带来较高的开销。我们的最终目标是提供硬件辅助的解决方案来提高云计算环境中的中间件性能。作为起点,在本文中,我们设计、实现和评估了用于加速 GC 操作的专用硬件指令。我们选择GC是因为它是虚拟机设计中的常见组件,并且会带来较高的性能和能耗开销。我们对各种 GC 算法进行了分析研究,以确定 GC 性能热点,这些热点占总 GC 执行时间的 50% 以上。通过将这些热点功能转移到硬件中,我们实现了一个数量级的加速并显着提高了能源效率。此外,我们的性能评估研究结果表明,硬件辅助 GC 指令可以将 GC 执行时间减少一半,使整体执行时间提高 7%。
Although virtualization technologies bring many benefits to cloud computing environments, as the virtual machines provide more features, the middleware layer has become bloated, introducing a high overhead. Our ultimate goal is to provide hardware-assisted solutions to improve the middleware performance in cloud computing environments. As a starting point, in this paper, we design, implement, and evaluate specialized hardware instructions to accelerate GC operations. We select GC because it is a common component in virtual machine designs and it incurs high performance and energy consumption overheads. We performed a profiling study on various GC algorithms to identify the GC performance hotspots, which contribute to more than 50% of the total GC execution time. By moving these hotspot functions into hardware, we achieved an order of magnitude speedup and significant improvement on energy efficiency. In addition, the results of our performance estimation study indicate that the hardware-assisted GC instructions can reduce the GC execution time by half and lead to a 7% improvement on the overall execution time.
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