Design and Resilience of Digital Circuits for Emerging Computing Paradigms
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".
Deadline for manuscript submissions: 15 October 2025 | Viewed by 97
Special Issue Editors
Interests: approximate computing; VLSI design; emerging computing model and paradigms; combinatorial optimization; neural networks
Special Issue Information
Dear Colleagues,
As Dennard scaling reaches its limits, the traditional advantages of technology scaling face significant challenges. Furthermore, modern applications demand increasingly complex computations, with power and energy consumption emerging as fundamental constraints on the scalability of computing performance. To address these challenges, there is growing interest in various emerging computing paradigms, including approximate computing, stochastic computing, neuromorphic computing, and Ising model-based computing. While these paradigms offer promising solutions for enhancing hardware efficiency, their continued advancement relies on developments spanning methodology, module design, architecture, system integration, and logic synthesis. Additionally, ensuring defect tolerance, fault tolerance, and reliability within these paradigms remains a formidable challenge. Modern applications such as machine learning, neural networks, and signal processing have already demonstrated the potential benefits of these computing approaches. Exploring strategies to more effectively leverage their hardware efficiency presents an exciting avenue for research.
This Special Issue aims to advance scholarly discourse, enhance the understanding of these paradigms' potential, and inspire future developments in the field.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:
- Approximate Computing
- Stochastic Computing
- Neuromorphic Computing
- Ising model-based Computing
- Machine Learning
- Theoretical Foundations for Emerging Computing Paradigms
- Hardware Design
- High-Level, Behavioral, and Logic Synthesis and Optimization
- Applications in Machine Learning, Signal Processing or Others
- Emerging Design Technologies for Future Computing
- Reliable and Secure Systems Design with Emerging Computing Paradigms
- Defect and Fault Tolerance for Systems
I look forward to receiving your contributions.
Dr. Tingting Zhang
Dr. Ke Chen
Guest Editors
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Keywords
- VLSI design
- approximate computing
- stochastic computing
- neuromorphic computing
- Ising model
- logic synthesis
- machine learning
- hardware design
- fault tolerance
- signal processing
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