ARXON: A Framework for Approximate Communication over Photonic Networks-on-Chip

Febin P. Sunny, Asif Mirza, Ishan Thakkar, Mahdi Nikdast, Sudeep Pasricha

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


The approximate computing paradigm advocates for relaxing accuracy goals in applications to improve energy-efficiency and performance. Recently, this paradigm has been explored to improve the energy-efficiency of silicon photonic networks-on-chip (PNoCs). Silicon photonic interconnects suffer from high power dissipation because of laser sources, which generate carrier wavelengths, and tuning power required for regulating photonic devices under different uncertainties. In this article, we propose a framework called AppRoXimation framework for On-chip photonic Networks (ARXON) to reduce such power dissipation overhead by enabling intelligent and aggressive approximation during communication over silicon photonic links in PNoCs. Our framework reduces laser and tuning-power overhead while intelligently approximating communication, such that application output quality is not distorted beyond an acceptable limit. Simulation results show that our framework can achieve up to 56.4% lower laser power consumption and up to 23.8% better energy-efficiency than the best-known prior work on approximate communication with silicon photonic interconnects and for the same application output quality.

Original languageEnglish
Article number9392111
Pages (from-to)1206-1219
Number of pages14
JournalIEEE Transactions on Very Large Scale Integration (VLSI) Systems
Issue number6
StatePublished - Jun 2021

Bibliographical note

Funding Information:
Manuscript received September 22, 2020; revised December 18, 2020 and February 17, 2021; accepted March 14, 2021. Date of publication March 31, 2021; date of current version June 4, 2021. This work was supported by the National Science Foundation (NSF) under Grant CCF-1813370 and Grant CCF-2006788. (Corresponding author: Sudeep Pasricha.) Febin P. Sunny, Asif Mirza, Mahdi Nikdast, and Sudeep Pasricha are with the Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80523 USA (e-mail: febin.sunny@;;;

Publisher Copyright:
© 1993-2012 IEEE.


  • Approximate computing
  • energy-efficiency
  • multilevel signaling
  • silicon photonic networks-on-chip (PNoCs)

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering


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