2027 International Conference on AI Chips and Semiconductor Design (AICSD 2027)

★CONTACT US
Website: www.aicsd.org
Date: October 15–17, 2027
Venue: China
Full Paper Submission: April 24, 2027
Email: info@aicsd.org
Tel:+86-28-85586839 (International)
Monday-Friday, 9:00am-12:00pm and 1:30pm-6:00pm


★Welcome to AICSD 2027
Taking place on October 15–17, 2027, the 2027 International Conference on AI Chips and Semiconductor Design (AICSD 2027) is a premier forum focused on driving breakthroughs in AI hardware and semiconductor innovation. The conference will convene chip architects, design engineers, researchers, and industry executives to share transformative ideas and real-world solutions shaping the next generation of intelligent computing systems.


★Publication Information
Registered and presented full papers will be included in the AICSD 2027 digital conference proceedings and submitted to major citation databases (including, but not limited to Ei Compendex and Scopus) for review and indexing.


★Call for papers
Topics of Interest include but not limited to:
1. AI Chip Architectures and Accelerators
NPUs, TPUs, and reconfigurable AI accelerators
In-memory and near-memory computing architectures

2. Design Automation, EDA, and AI-Driven IC Design
AI/ML-assisted EDA for logic synthesis, placement, and routing
RL-driven chip floorplanning and physical design optimization

3. Advanced Semiconductor Devices and Process Technologies
Sub-3nm logic devices: GAA-FETs, CFETs, and 2D material transistors
Advanced lithography (EUV, high-NA EUV) and patterning techniques

4. System-Level Integration and Software-Hardware Co-Design
Chiplet-based SiP and advanced packaging (2.5D/3D)
Compiler and runtime optimization for AI accelerators

5. Memory Technologies and Storage for AI Systems
Emerging non-volatile memories (MRAM, ReRAM, PCM) and logic integration
HBM, processing-in-memory (PIM), and memory-centric architectures

6. Emerging Paradigms, Reliability, and Security
Neuromorphic computing and spiking neural network (SNN) hardware
Quantum, optical, and analog AI accelerators