Machine Learning in Network-on-Chip Architectures

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 16 July 2024 | Viewed by 374

Special Issue Editors


E-Mail Website
Guest Editor
Electrical and Computer Engineering Department, University of Victoria, Victoria, BC V8W 3P6, Canada
Interests: computer architecture; network on chip; silicon photonics; machine learning

E-Mail Website
Guest Editor
Electrical and Computer Engineering Department, University of Victoria, Victoria, BC V8W 3P6, Canada
Interests: network-on-chips, wireless communications, high performance architectures

Special Issue Information

Dear Colleagues,

We cordially invite you to submit your papers for the MDPI Electronics (IF=2.9) special issue on "Machine Learning in Network-on-Chip (NoC) Architectures". The goal of this special issue is to explore the intersection of machine learning and NoC architectures and present the latest advancements, applications, and challenges as they relate to this exciting area.

Network-on-Chip architectures have emerged as a promising solution for efficient communication in complex system-on-chip designs. Artificial intelligence and machine learning have grown rapidly in recent years, and their integration into NoC architectures is becoming increasingly important. NoC designs can benefit from machine learning techniques in many ways, including performance optimization, energy efficiency, fault tolerance, and resource allocation.

The scope includes, but is not limited to, the following:

  1. Machine learning-based routing algorithms for NoCs
  2. Deep learning techniques for congestion and deadlock avoidance
  3. Neural network models for adaptive flow control in NoCs
  4. Reinforcement learning approaches for fault-tolerant NoC designs
  5. Dependable system design in Nocs with machine learning techniques
  6. Machine learning-based power optimization in NoC architectures
  7. Data-driven approaches for NoC design exploration and optimization
  8. AI-driven resource allocation and management in NoCs
  9. Case studies and applications of machine learning in different NoC architectures such as electrical, optical and wireless.

Dr. Meisam Abdollahi
Dr. Amir Baharloo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning
  • artificial intelligence
  • network-on-chip
  • multi/many-core systems
  • high performance
  • power efficiency
  • reliable on-chip communication

Published Papers

This special issue is now open for submission.
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