• Media type: E-Article
  • Title: TB-TBP: a task-based adaptive routing algorithm for network-on-chip in heterogenous CPU-GPU architectures
  • Contributor: Fang, Juan; Wei, Zhichao; Liu, Yaqi; Hou, Yumin
  • imprint: Springer Science and Business Media LLC, 2024
  • Published in: The Journal of Supercomputing
  • Language: English
  • DOI: 10.1007/s11227-023-05700-7
  • ISSN: 0920-8542; 1573-0484
  • Keywords: Hardware and Architecture ; Information Systems ; Theoretical Computer Science ; Software
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>With the rapid development of heterogeneous network-on-chip (NoC), a vast amount of shared resources are integrated into NoC. Intense resource competition exists between CPUs and GPUs, leading to congestion and a decrease in overall network performance. Reasonable node placement can minimize network conflicts at the topology level. This paper first discusses the placement of shared last-level cache and memory controller, then selects a more rational placement method and optimizes the path. To solve the hot spots problem in center placement method, a task-based routing algorithm is designed to plan the path. Simulation results demonstrate that, compared to the traditional routing algorithm, the overall network latency is reduced by 9%, and the CPU performance is improved by 13.6%. Furthermore, a dynamic task-based routing algorithm is proposed. Compared to the static task routing algorithm, the overall network latency is reduced by 2.08%, and the CPU performance is improved by 4.09%.</jats:p>