• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2025, Vol. 47 ›› Issue (5): 797-810.

• 高性能计算 • 上一篇    下一篇

面向数据密集型应用的近数据处理架构设计

谢洋,李晨,陈小文   

  1. (国防科技大学计算机学院,湖南 长沙 410073)
  • 收稿日期:2024-03-13 修回日期:2024-06-07 出版日期:2025-05-25 发布日期:2025-05-27
  • 基金资助:
    国家自然科学基金(62202478)

A near-data processing architecture for data-intensive applications

XIE Yang,LI Chen,CHEN Xiaowen   

  1. (College of Computer Science and Technology,National University of Defense Technology,Changsha 410073,China)
  • Received:2024-03-13 Revised:2024-06-07 Online:2025-05-25 Published:2025-05-27

摘要: 大数据时代,多核处理器在处理数据密集型应用时,面临着数据局部性低、访存延迟高和内核计算效率低等挑战。近数据处理对于降低访存延迟、提高内核计算效率具有重要潜力。设计了一种计算访存松耦合的近数据处理架构(LcNDP),部署在多核处理器的共享缓存端和内存端。一方面通过迁移内核的访存任务,实现内核计算与访存的并行,隐藏访存开销;另一方面通过近数据计算单元,处理流数据计算,降低内核计算量和访存开销。实验结果表明LcNDP相较于传统多核架构,平均延迟降低了43%,与传统近数据处理的多核架构相比平均延迟降低了23%。

关键词: 近数据, 数据密集型应用, 计算机体系结构, 多核处理器

Abstract: In the era of big data, multi-core processors face significant challenges when handling data-intensive applications, including low data locality, high memory access latency, and inefficient core utilization. Near-data processing (NDP) holds great potential for reducing memory latency and improving computational efficiency. This paper proposes a loosely-coupled near-data processing architecture (LcNDP), deployed at both the shared cache level and memory controller of multi-core processors. The key innovations include: Offloading memory access tasks from compute cores to enable parallel execution of computation and memory operations, thereby hiding memory latency. Processing streaming data via near-data compute units to reduce both computational and memory overhead on the cores. Experimental results demonstrate that, compared to traditional multi-core architectures, LcNDP achieves an average 43% reduction in latency. When benchmarked against conventional NDP-enhanced multi-core designs, it further delivers a 23% average latency improvement.

Key words: near-data processing (NDP), data-intensive application, computer architecture, multi-core processor