How can Garbage Collection be energy efficient by dynamic offloading?

Jie Tang, Chen Liu, J. Gaudiot
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Abstract

Garbage Collection (GC) is still a major issue in JVM for both mobile and cluster computing. GC offloading is proposed to improve the performance of GC by delivering part or all of the operations into another dedicated GC hardware. However, the traditional offloading just offloads directly not considering the phase change of GC behavior, which can be classified into two different groups: minor GC and major GC. The minor GC is fast and frequently invoked, while major GC is expensive in terms of time but seldom takes place. The direct offloading made GC workload frequently hopping between main processor and GC hardware, introduced a noticeable overhead and offset any possible benefits of workload loading. To solve this issue, we propose to offload GC dynamically by a careful selection of profitable and harmful GC operations. We also made a case study on Apache Spark, a lightning-fast cluster computing platform. It shows dynamic offloading can yield nearly 42.6% performance improvement with a concurrent 32.1% in energy cost reduction.
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垃圾收集如何通过动态卸载实现节能?
对于移动和集群计算,垃圾收集(GC)仍然是JVM中的一个主要问题。GC卸载被提议通过将部分或全部操作交付到另一个专用GC硬件来提高GC的性能。然而,传统的卸载只是直接卸载,而不考虑GC行为的相变,这可以分为两种不同的类型:次要GC和主要GC。次要GC快速且经常被调用,而主要GC在时间上很昂贵,但很少发生。直接卸载使GC工作负载频繁地在主处理器和GC硬件之间跳转,带来了明显的开销,并抵消了工作负载负载可能带来的任何好处。为了解决这个问题,我们建议通过仔细选择有利的和有害的GC操作来动态卸载GC。我们还对Apache Spark进行了案例研究,这是一个闪电般的集群计算平台。结果表明,动态卸载可以提高42.6%的性能,同时降低32.1%的能源成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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