ALPHA: A hybrid topology for memory-centric network

Jiaxiang Li, Huaxi Gu, Shixiong Qi, Haoran Wang, Kang Wang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Memory system, as the basic constituent of the computing system, has a inevitable impact on the system performance. Traditional bus-based memory access system cannot fulfill the performance requirement of the future high-performance computing system due to its limitation on energy-efficiency. Memory-centric network (MCN) is considered as a promising candidate for future system interconnect. To improve the energyefficiency of memory access system by utilizing MCN, the topology of MCN needs to be carefully designed, as interconnection links take a huge part of power consumption. In this letter, we propose a new memory network topology named ALPHA. ALPHA is a 2-D topology. As ALPHA employs different types of interconnection links in the X-dimension and the Ydimension, respectively, it can maintain high throughput while using fewer links. Besides we redesign the switch of HMC for its implementation in ALPHA. We make a comparison between ALPHA and four popular topologies. The simulation results show that ALPHA greatly increases throughput and decreases latency.

Original languageEnglish
Article number20181108
JournalIEICE Electronics Express
Volume16
Issue number4
DOIs
StatePublished - 2019

Bibliographical note

Publisher Copyright:
© IEICE 2019.

Funding

This work was supported by the National Science Foundation of China under Grants 61634004, and Grant 61472300, the Fundamental Research Funds for the Central Universities Grant No. JB180309 and No. JB170107, and the key research and development plan of Shaanxi province No. 2017ZDCXL-GY-05-01.

FundersFunder number
National Natural Science Foundation of China (NSFC)61472300, 61634004
Fundamental Research Funds for the Central UniversitiesJB180309

    Keywords

    • Hybrid memory cube
    • Memory-centric network
    • Topology

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Electrical and Electronic Engineering

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