An Approximate Communication Framework for Network-on-Chips

Yuechen Chen, Ahmed Louri

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Current multi-/many-core systems spend large amounts of time and power transmitting data across on-chip interconnects. This problem is aggravated when data-intensive applications, such as machine learning and pattern recognition, are executed in these systems. Recent studies show that some data-intensive applications can tolerate modest errors, thus opening a new design dimension, namely, trading result quality for better system performance. In this article, we explore application error tolerance and propose an approximate communication framework to reduce the power consumption and latency of network-on-chips (NoCs). The proposed framework incorporates a quality control method and a data approximation mechanism to reduce the packet size to decrease network power consumption and latency. The quality control method automatically identifies the error-resilient variables that can be approximated during transmission and calculates their error thresholds based on the quality requirements of the application by analyzing the source code. The data approximation method includes a lightweight lossy compression scheme, which significantly reduces packet size when the error-resilient variables are transmitted. This framework results in fewer flits in each data packet and reduces traffic in NoCs while guaranteeing the quality requirements of applications. Our cycle-accurate simulation using the AxBench benchmark suite shows that the proposed approximate communication framework achieves 62 percent latency reduction and 43 percent dynamic power reduction compared to previous approximate communication techniques while ensuring 95 percent result quality.

Original languageEnglish (US)
Article number8966491
Pages (from-to)1434-1446
Number of pages13
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number6
StatePublished - Jun 1 2020
Externally publishedYes


  • Approximate communication
  • error control
  • network-on-chips (NoCs)
  • power consumption

ASJC Scopus subject areas

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


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