133 citations · 300 across the 30 of their papers we have counts for
32 papers
Scalar Perturbations and Induced Gravitational Waves from First-Order Phase Transitions in Lattice Simulations
Yuan-Jie Li, Jing Liu, Zhuan Ning +3
Cosmological first-order phase transitions can generate curvature perturbations through inhomogeneous quantum tunneling, as studied previously on superhorizon scales. In this work,…
WaveletECO: A Closed-Loop Physical ECO Platform and a Specialized Local Language Model
Guoxiang Xu, Guozhen Ji, Zijian Luo +3
Engineering change order (ECO) is an important step in repairing timing and electrical violations during the late stages of chip design. Existing Agentic EDA methods primarily focu…
Circuit-MLLM: Topological Logic-Guided Latent-Space Visual Reasoning for Circuit Schematic Understanding
Jinyuan Deng, Yuqi Jiang, Wenjing Huang +3
Through pre-training on extensive text and image datasets, current multi-modal large language models (MLLMs) achieve strong performance on general tasks. However, circuit schematic…
RODE: A Radial-Orthogonal Decoupled Engine for Optimization
Guoxiang Xu, Bince Qu, Qi Sun +1
Modern neural network training increasingly uses matrix-aware optimizers, yet their conditioned matrix step is typically added directly to the weight, jointly changing its norm and…
Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows
Jinyuan Deng, Zhengrui Chen, Xufeng Wei +4
Large language model (LLM) agents are extending electronic design automation (EDA) beyond static RTL generation toward long-horizon, tool-interactive workflows. Yet it remains uncl…
FactorHD: A Hyperdimensional Computing Model for Multi-Object Multi-Class Representation and Factorization
Yifei Zhou, Xuchu Huang, Chenyu Ni +4
Neuro-symbolic artificial intelligence (neuro-symbolic AI) excels in logical analysis and reasoning. Hyperdimensional Computing (HDC), a promising brain-inspired computational mode…
TReCiM: Lower Power and Temperature-Resilient Multibit 2FeFET-1T Compute-in-Memory Design
Yifei Zhou, Thomas Kämpfe, Kai Ni +3
Compute-in-memory (CiM) emerges as a promising solution to solve hardware challenges in artificial intelligence (AI) and the Internet of Things (IoT), particularly addressing the "…
C-Nash: A Novel Ferroelectric Computing-in-Memory Architecture for Solving Mixed Strategy Nash Equilibrium
Yu Qian, Kai Ni, Thomas Kämpfe +2
The concept of Nash equilibrium (NE), pivotal within game theory, has garnered widespread attention across numerous industries. Recent advancements introduced several quantum Nash…
Classification-Based Automatic HDL Code Generation Using LLMs
Wenhao Sun, Bing Li, Grace Li Zhang +3
While large language models (LLMs) have demonstrated the ability to generate hardware description language (HDL) code for digital circuits, they still suffer from the hallucination…
Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models
Kangwei Xu, Grace Li Zhang, Xunzhao Yin +3
In High-Level Synthesis (HLS), converting a regular C/C++ program into its HLS-compatible counterpart (HLS-C) still requires tremendous manual effort. Various program scripts have…
BasisN: Reprogramming-Free RRAM-Based In-Memory-Computing by Basis Combination for Deep Neural Networks
Amro Eldebiky, Grace Li Zhang, Xunzhao Yin +4
Deep neural networks (DNNs) have made breakthroughs in various fields including image recognition and language processing. DNNs execute hundreds of millions of multiply-and-accumul…
FabGPT: An Efficient Large Multimodal Model for Complex Wafer Defect Knowledge Queries
Yuqi Jiang, Xudong Lu, Qian Jin +3
Intelligence is key to advancing integrated circuit (IC) fabrication. Recent breakthroughs in Large Multimodal Models (LMMs) have unlocked extraditionary abilities in understanding…
LiveMind: Low-latency Large Language Models with Simultaneous Inference
Chuangtao Chen, Grace Li Zhang, Xunzhao Yin +3
In this paper, we introduce LiveMind, a novel low-latency inference framework for large language model (LLM) inference which enables LLMs to perform inferences with incomplete user…
EncodingNet: A Novel Encoding-based MAC Design for Efficient Neural Network Acceleration
Bo Liu, Grace Li Zhang, Xunzhao Yin +2
Deep neural networks (DNNs) have achieved great breakthroughs in many fields such as image classification and natural language processing. However, the execution of DNNs needs to c…
FeReX: A Reconfigurable Design of Multi-bit Ferroelectric Compute-in-Memory for Nearest Neighbor Search
Zhicheng Xu, Che-Kai Liu, Chao Li +7
Rapid advancements in artificial intelligence have given rise to transformative models, profoundly impacting our lives. These models demand massive volumes of data to operate effec…
Low Power and Temperature-Resilient Compute-In-Memory Based on Subthreshold-FeFET
Yifei Zhou, Xuchu Huang, Jianyi Yang +4
Compute-in-memory (CiM) is a promising solution for addressing the challenges of artificial intelligence (AI) and the Internet of Things (IoT) hardware such as 'memory wall' issue.…
Reconfigurable Frequency Multipliers Based on Complementary Ferroelectric Transistors
Haotian Xu, Jianyi Yang, Cheng Zhuo +3
Frequency multipliers, a class of essential electronic components, play a pivotal role in contemporary signal processing and communication systems. They serve as crucial building b…
OplixNet: Towards Area-Efficient Optical Split-Complex Networks with Real-to-Complex Data Assignment and Knowledge Distillation
Ruidi Qiu, Amro Eldebiky, Grace Li Zhang +4
Having the potential for high speed, high throughput, and low energy cost, optical neural networks (ONNs) have emerged as a promising candidate for accelerating deep learning tasks…
Class-Aware Pruning for Efficient Neural Networks
Mengnan Jiang, Jingcun Wang, Amro Eldebiky +4
Deep neural networks (DNNs) have demonstrated remarkable success in various fields. However, the large number of floating-point operations (FLOPs) in DNNs poses challenges for thei…
SEE-MCAM: Scalable Multi-bit FeFET Content Addressable Memories for Energy Efficient Associative Search
Shengxi Shou, Che-Kai Liu, Sanggeon Yun +7
In this work, we propose SEE-MCAM, scalable and compact multi-bit CAM (MCAM) designs that utilize the three-terminal ferroelectric FET (FeFET) as the proxy. By exploiting the multi…
A Ferroelectric Compute-in-Memory Annealer for Combinatorial Optimization Problems
Xunzhao Yin, Yu Qian, Alptekin Vardar +11
Computationally hard combinatorial optimization problems (COPs) are ubiquitous in many applications, including logistical planning, resource allocation, chip design, drug explorati…
Computational and Storage Efficient Quadratic Neurons for Deep Neural Networks
Chuangtao Chen, Grace Li Zhang, Xunzhao Yin +3
Deep neural networks (DNNs) have been widely deployed across diverse domains such as computer vision and natural language processing. However, the impressive accomplishments of DNN…
A Survey on Approximate Multiplier Designs for Energy Efficiency: From Algorithms to Circuits
Ying Wu, Chuangtao Chen, Weihua Xiao +6
Given the stringent requirements of energy efficiency for Internet-of-Things edge devices, approximate multipliers, as a basic component of many processors and accelerators, have b…
GANDSE: Generative Adversarial Network based Design Space Exploration for Neural Network Accelerator Design
Lang Feng, Wenjian Liu, Chuliang Guo +3
With the popularity of deep learning, the hardware implementation platform of deep learning has received increasing interest. Unlike the general purpose devices, e.g., CPU, or GPU,…