All-To-All Broadcast in Hexagonal Torus Networks On-Chip

Abderezak Touzene*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Hexagonal torus networks are special family of Eisenstein-Jacobi (EJ) networks which have gained popularity as goodcandidates network On-Chip (NoC) for interconnecting Multiprocessor System-on-Chips (MPSoCs). They showed better topological properties compared to the 2D torus networks with the same number of nodes. All-to-all broadcast is a collective communicationalgorithm used frequently in some parallel applications. Recently, an off-chip all-to-all broadcast algorithm has been proposed forhexagonal torus networks assuming half-duplex links and all-ports communication. The proposed all-to-all broadcast algorithm does not achieve the minimum transmission time and requires 24 k extra buffers, where k is the network diameter. We first extend this work by proposing an efficient all-to-all broadcast on hexagonal torus networks under full-duplex links and all-ports communications assumptions which achieves the minimum transmission delay but requires 36 k extra buffers per router. In a second stage, we develop a new all-to-all broadcast more suitable for hexagonal torus network on-chip that achieves optimal transmission delay time without requiring any extra buffers per router. By reducing the amount of buffer space, the new all-to-all broadcast reduces the routers cost which is an important issue in NoCs architectures.

Original languageEnglish
Article number6881698
Pages (from-to)2410-2420
Number of pages11
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number9
Publication statusPublished - Sept 1 2015


  • Eisenstein-Jacobi networks
  • Network-on-Chip (NoC)
  • all-to-all broadcast
  • hexagonal mesh
  • spanning trees

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


Dive into the research topics of 'All-To-All Broadcast in Hexagonal Torus Networks On-Chip'. Together they form a unique fingerprint.

Cite this