A survey of machine learning for computer architecture and systems
It has been a long time that computer architecture and systems are optimized for efficient
execution of machine learning (ML) models. Now, it is time to reconsider the relationship …
execution of machine learning (ML) models. Now, it is time to reconsider the relationship …
Two‐Dimensional Semiconductors: From Device Processing to Circuit Integration
C Sheng, X Dong, Y Zhu, X Wang… - Advanced Functional …, 2023 - Wiley Online Library
The atomically thin nature and exceptional electrical properties of 2D materials (2DMs) have
garnered significant interest in circuit applications. Researchers have developed circuits …
garnered significant interest in circuit applications. Researchers have developed circuits …
Chipnemo: Domain-adapted llms for chip design
M Liu, TD Ene, R Kirby, C Cheng, N Pinckney… - arXiv preprint arXiv …, 2023 - arxiv.org
ChipNeMo aims to explore the applications of large language models (LLMs) for industrial
chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we …
chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we …
IronMan-Pro: Multiobjective design space exploration in HLS via reinforcement learning and graph neural network-based modeling
Despite the great success of high-level synthesis (HLS) tools, we observe several
unresolved challenges: 1) the high-level abstraction of HLS programming styles sometimes …
unresolved challenges: 1) the high-level abstraction of HLS programming styles sometimes …
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 …
Putting humans back in the loop: An affordance conceptualization of the 4th industrial revolution
The current technology epoch—sometimes called the fourth industrial revolution (4IR)—
involves the innovative application of rapidly advancing digital technologies such as artificial …
involves the innovative application of rapidly advancing digital technologies such as artificial …
A review of machine learning techniques in analog integrated circuit design automation
Analog integrated circuit design is widely considered a time-consuming task due to the
acute dependence of analog performance on the transistors' and passives' dimensions. An …
acute dependence of analog performance on the transistors' and passives' dimensions. An …
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 …
Graph neural networks: A powerful and versatile tool for advancing design, reliability, and security of ICs
Graph neural networks (GNNs) have pushed the state-of-the-art (SOTA) for performance in
learning and predicting on large-scale data present in social networks, biology, etc. Since …
learning and predicting on large-scale data present in social networks, biology, etc. Since …
Robust GNN-based representation learning for HLS
The efficient and timely optimization of microarchitecture for a target application is hindered
by the long evaluation runtime of a design candidate, creating a serious burden. To tackle …
by the long evaluation runtime of a design candidate, creating a serious burden. To tackle …