Low-Latency High-Bandwidth Interconnection Networks by Selective Packet Compression

Naoya Niwa, H. Amano, M. Koibuchi
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引用次数: 1

Abstract

Interconnection network ideally transfers the maximum amount of communication dataset within the least amount of time to fully exploit the parallelism of target applications on parallel computer systems. To this goal, we propose a selective data-compression interconnection network. Data compression virtually increases the effective network bandwidth, while each compute node introduces additional latency overhead to perform (de-)compression operation to end-to-end communication latency. To minimize the effect of the compression latency overhead on the end-to-end communication latency, we selectively apply a compression technique to a packet. The compression operation is taken for long packets and is also taken when network congestion is detected at a network interface. Evaluation results show that simple lossless and lossy compression algorithms have up to 3.0 and 1.8 compression ratios for integer and floating-point communication data in some parallel applications, respectively, while the lossy compression algorithm successfully satisfies the required quality of results. Through a cycle-network simulation, the selective compression method using the above compression algorithms improves by up to 46% the network throughput with the moderate increase of the communication latency of short packets.
选择性分组压缩的低延迟高带宽互连网络
互连网络理想地在最短的时间内传输最大数量的通信数据集,以充分利用并行计算机系统上目标应用程序的并行性。为此,我们提出了一种选择性数据压缩互连网络。数据压缩实际上增加了有效的网络带宽,而每个计算节点为执行(解)压缩操作引入了额外的延迟开销,从而增加了端到端通信延迟。为了最小化压缩延迟开销对端到端通信延迟的影响,我们有选择地对数据包应用压缩技术。压缩操作用于长数据包,当在网络接口检测到网络拥塞时也会进行压缩操作。评估结果表明,在一些并行应用中,简单的无损压缩算法和有损压缩算法对整数和浮点通信数据的压缩比分别高达3.0和1.8,而有损压缩算法成功地满足了所要求的结果质量。通过循环网络仿真,使用上述压缩算法的选择性压缩方法在适度增加短数据包通信延迟的情况下,提高了高达46%的网络吞吐量。
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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