A low-latency memory-cube network with dual diagonal mesh topology and bypassed pipelines

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Concurrency and Computation-Practice & Experience Pub Date : 2024-09-23 DOI:10.1002/cpe.8290
Masashi Oda, Kai Keida, Ryota Yasudo
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Abstract

A memory cube network is an interconnection network composed of 3D stacked memories called memory cubes. By exploiting a packet switching, it can provide fast memory accesses to a large number of memory cubes. Although interconnection networks have been studied in many years for supercomputers and data centers, existing technologies are difficult to apply to memory cube networks. This is because the link length and the number of ports are limited, and hence the hop count increases. In this article, we propose a dual diagonal mesh (DDM), a layout-oriented memory-cube network. Furthermore, we propose the routing algorithm and the router architecture with bypassed pipelines for DDM. Our experimental results demonstrate that our routing and router architecture with bypassed pipelines reduces the memory access latency. We implement four router architectures and evaluate them with the traffic patterns derived from the NAS parallel benchmark.

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采用双对角网状拓扑结构和旁路管道的低延迟内存立方体网络
内存立方体网络是由称为内存立方体的三维堆叠存储器组成的互连网络。通过利用分组交换,它可以为大量内存立方体提供快速内存访问。尽管多年来人们一直在研究超级计算机和数据中心的互连网络,但现有技术很难应用于内存立方网络。这是因为链路长度和端口数量有限,因此跳数增加。在本文中,我们提出了一种面向布局的内存立方体网络--双对角网格(DDM)。此外,我们还提出了 DDM 的路由算法和带有旁路管道的路由器架构。实验结果表明,我们的路由和带旁路流水线的路由器架构降低了内存访问延迟。我们实现了四种路由器架构,并利用 NAS 并行基准得出的流量模式对它们进行了评估。
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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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