IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
Scope & Guideline
Connecting Knowledge with Cutting-Edge Design Practices
Introduction
Aims and Scopes
- Integrated Circuit Design and Automation:
The journal covers all aspects of integrated circuit design, including automation tools, methodologies for circuit synthesis, layout, and verification. - Hardware Security:
There is a significant focus on hardware security, including the detection and mitigation of hardware trojans, side-channel attacks, and other vulnerabilities in integrated circuits. - Machine Learning and AI in Design:
The integration of machine learning and artificial intelligence techniques into CAD processes is a key area, exploring how these technologies can optimize design workflows and enhance system performance. - Emerging Technologies:
The journal addresses advancements in emerging technologies such as quantum computing, memristor-based systems, and neuromorphic computing, providing insights into their design implications. - Energy-Efficient and Reliable Design:
Research on energy-efficient design methodologies and reliability analysis is prominent, focusing on sustainable practices in circuit design and the performance of various electronic systems. - Interdisciplinary Approaches:
The journal encourages interdisciplinary research that combines aspects of electrical engineering, computer science, and applied mathematics to solve complex design challenges.
Trending and Emerging
- Hardware Security and Trust:
Recent publications indicate a rising trend in research focused on hardware security measures, including advanced techniques for detecting hardware trojans and protecting against side-channel attacks. - Machine Learning and AI Applications:
There is a significant increase in studies applying machine learning and artificial intelligence to various aspects of design automation, including optimization of design processes and predictive modeling. - Energy-Efficient Design Techniques:
Research dedicated to energy-efficient design methodologies is on the rise, reflecting a growing awareness of sustainability and power management in integrated circuits. - Processing-In-Memory Architectures:
Emerging themes around processing-in-memory architectures highlight their potential to enhance performance in deep learning and data-intensive applications, marking a shift in design paradigms. - Quantum Computing Design:
An increasing number of papers are addressing the design challenges associated with quantum computing, including circuit synthesis and optimization for quantum architectures. - Neuromorphic Computing Systems:
There is a growing interest in neuromorphic computing, with research focusing on the design and optimization of circuits that mimic neural behavior for advanced computational tasks.
Declining or Waning
- Traditional Analog Design Approaches:
There has been a noticeable decline in papers addressing conventional analog circuit design techniques, as the focus shifts toward digital and mixed-signal designs that leverage advanced technologies. - Basic Circuit Synthesis Techniques:
Basic synthesis techniques that do not incorporate modern advancements or machine learning approaches are becoming less common, as researchers seek more sophisticated methods. - Static Timing Analysis:
While still important, traditional static timing analysis topics are being overshadowed by more dynamic approaches that incorporate machine learning and real-time analysis. - Low-Level Hardware Description Languages:
The use of low-level hardware description languages (HDLs) is declining as higher-level abstractions and automated tools are preferred for their efficiency and ease of use. - Single-Technology Focus:
Research that focuses solely on one technology or methodology without considering the integration of multiple technologies is decreasing, as there is a growing emphasis on cross-platform and multi-technology solutions.
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