Chip-chat: Challenges and opportunities in conversational hardware design
Modern hardware design starts with specifications provided in natural language. These are
then translated by hardware engineers into appropriate Hardware Description Languages …
then translated by hardware engineers into appropriate Hardware Description Languages …
Artificial intelligence for safety-critical systems in industrial and transportation domains: A survey
Artificial Intelligence (AI) can enable the development of next-generation autonomous safety-
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …
[图书][B] VLSI physical design: from graph partitioning to timing closure
The electronic design automation (EDA) industry develops software to support engineers in
the creation of new integrated circuit (IC) designs. Due to the high complexity of modern …
the creation of new integrated circuit (IC) designs. Due to the high complexity of modern …
A survey of reasoning with foundation models
Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-
world settings such as negotiation, medical diagnosis, and criminal investigation. It serves …
world settings such as negotiation, medical diagnosis, and criminal investigation. It serves …
Rtllm: An open-source benchmark for design rtl generation with large language model
Y Lu, S Liu, Q Zhang, Z Xie - 2024 29th Asia and South Pacific …, 2024 - ieeexplore.ieee.org
Inspired by the recent success of large language models (LLMs) like ChatGPT, researchers
start to explore the adoption of LLMs for agile hardware design, such as generating design …
start to explore the adoption of LLMs for agile hardware design, such as generating design …
A survey on machine learning accelerators and evolutionary hardware platforms
Advanced computing systems have long been enablers for breakthroughs in artificial
intelligence (AI) and machine learning (ML) algorithms, either through sheer computational …
intelligence (AI) and machine learning (ML) algorithms, either through sheer computational …
A survey of graph neural networks for electronic design automation
Driven by Moore's law, the chip design complexity is steadily increasing. Electronic Design
Automation (EDA) has been able to cope with the challenging very large-scale integration …
Automation (EDA) has been able to cope with the challenging very large-scale integration …
Circuitnet: An open-source dataset for machine learning in vlsi cad applications with improved domain-specific evaluation metric and learning strategies
The design automation community has been actively exploring machine learning (ML) for
very-large-scale-integrated (VLSI) computer-aided design (CAD). Many studies have …
very-large-scale-integrated (VLSI) computer-aided design (CAD). Many studies have …
A comprehensive survey on electronic design automation and graph neural networks: Theory and applications
Driven by Moore's law, the chip design complexity is steadily increasing. Electronic Design
Automation (EDA) has been able to cope with the challenging very large-scale integration …
Automation (EDA) has been able to cope with the challenging very large-scale integration …
Functionality matters in netlist representation learning
Learning feasible representation from raw gate-level netlists is essential for incorporating
machine learning techniques in logic synthesis, physical design, or verification. Existing …
machine learning techniques in logic synthesis, physical design, or verification. Existing …