17 citations · 47 across the 37 of their papers we have counts for
38 papers
Beyond Feature Reliability: Repeat-Informed Multifractal Curve Regression for Brain-Age Prediction
Yu Chang, Anzhe Cheng, Jiahao Chen +8
Brain-age prediction from resting-state fMRI provides a quantitative framework for characterizing age-related changes in spontaneous brain dynamics and for identifying functional s…
AgentIR: A Workload-Adaptive Cascade Retrieval Substrate for Long-Term Conversational Memory
Aojie Yuan, Haiyue Zhang, Shahin Nazarian
Long-term conversational memory is a retrieval workload classical IR was not built for: the index grows during the query stream, query types shift intra-session, and the latency bu…
POET: Power-Oriented Evolutionary Tuning for LLM-Based RTL PPA Optimization
Heng Ping, Peiyu Zhang, Zhenkun Wang +5
Applying large language models (LLMs) to RTL code optimization for improved power, performance, and area (PPA) faces two key challenges: ensuring functional correctness of optimize…
EMoE: Eigenbasis-Guided Routing for Mixture-of-Experts
Anzhe Cheng, Shukai Duan, Shixuan Li +5
The relentless scaling of deep learning models has led to unsustainable computational demands, positioning Mixture-of-Experts (MoE) architectures as a promising path towards greate…
ERMoE: Eigen-Reparameterized Mixture-of-Experts for Stable Routing and Interpretable Specialization
Anzhe Cheng, Shukai Duan, Shixuan Li +8
Mixture-of-Experts (MoE) architectures expand model capacity by sparsely activating experts but face two core challenges: misalignment between router logits and each expert's inter…
SuperSNN: A Hardware-Aware Framework for Physically Realizable, High-Performance Superconducting Spiking Neural Network Chips
Changxu Song, Arda Caliskan, Beyza Zeynep Ucpinar +5
Despite numerous proposed designs for superconducting neural networks (SNNs), most have overlooked practical fabrication constraints, leading to implementations limited to only a f…
Eigen Neural Network: Unlocking Generalizable Vision with Eigenbasis
Anzhe Cheng, Chenzhong Yin, Mingxi Cheng +3
The remarkable success of Deep Neural Networks(DNN) is driven by gradient-based optimization, yet this process is often undermined by its tendency to produce disordered weight stru…
HDLCoRe: A Training-Free Framework for Mitigating Hallucinations in LLM-Generated HDL
Heng Ping, Shixuan Li, Peiyu Zhang +8
Recent advances in large language models (LLMs) have demonstrated remarkable capabilities in code generation tasks. However, when applied to hardware description languages (HDL), t…
MaskAttn-UNet: A Mask Attention-Driven Framework for Universal Low-Resolution Image Segmentation
Anzhe Cheng, Chenzhong Yin, Yu Chang +4
Low-resolution image segmentation is crucial in real-world applications such as robotics, augmented reality, and large-scale scene understanding, where high-resolution data is ofte…
Exploiting Application-to-Architecture Dependencies for Designing Scalable OS
Yao Xiao, Nikos Kanakaris, Anzhe Cheng +5
With the advent of hundreds of cores on a chip to accelerate applications, the operating system (OS) needs to exploit the existing parallelism provided by the underlying hardware r…
A Structure-Aware Framework for Learning Device Placements on Computation Graphs
Shukai Duan, Heng Ping, Nikos Kanakaris +9
Computation graphs are Directed Acyclic Graphs (DAGs) where the nodes correspond to mathematical operations and are used widely as abstractions in optimizations of neural networks.…
Unlocking Deep Learning: A BP-Free Approach for Parallel Block-Wise Training of Neural Networks
Anzhe Cheng, Zhenkun Wang, Chenzhong Yin +5
Backpropagation (BP) has been a successful optimization technique for deep learning models. However, its limitations, such as backward- and update-locking, and its biological impla…
PerfRL: A Small Language Model Framework for Efficient Code Optimization
Shukai Duan, Nikos Kanakaris, Xiongye Xiao +8
Code optimization is a challenging task requiring a substantial level of expertise from developers. Nonetheless, this level of human capacity is not sufficient considering the rapi…
Leader-Follower Neural Networks with Local Error Signals Inspired by Complex Collectives
Chenzhong Yin, Mingxi Cheng, Xiongye Xiao +4
The collective behavior of a network with heterogeneous, resource-limited information processing units (e.g., group of fish, flock of birds, or network of neurons) demonstrates hig…
A Majority Logic Synthesis Framework For Single Flux Quantum Circuits
Junyao Zhang, Paul Bogdan, Shahin Nazarian
Exascale computing and its associated applications have required increasing degrees of efficiency. Semiconductor-Transistor-based Circuits (STbCs) have struggled with increasing th…
C-SAR: SAT Attack Resistant Logic Locking for RSFQ Circuits
Junyao Zhang, Paul Bogdan, Shahin Nazarian
Since the development of semiconductor technologies, exascale computing and its associated applications have required increasing degrees of efficiency. Semiconductor-transistor-bas…
End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning
Yao Xiao, Guixiang Ma, Nesreen K. Ahmed +4
To enable heterogeneous computing systems with autonomous programming and optimization capabilities, we propose a unified, end-to-end, programmable graph representation learning (P…
Trust-aware Control for Intelligent Transportation Systems
Mingxi Cheng, Junyao Zhang, Shahin Nazarian +2
Many intelligent transportation systems are multi-agent systems, i.e., both the traffic participants and the subsystems within the transportation infrastructure can be modeled as i…
Practice Problems for Hardware Engineers
Shahin Nazarian
This book is to help undergraduate and graduate students of electrical and computer engineering disciplines with their job interviews. It may also be used as a practice resource wh…
VRoC: Variational Autoencoder-aided Multi-task Rumor Classifier Based on Text
Mingxi Cheng, Shahin Nazarian, Paul Bogdan
Social media became popular and percolated almost all aspects of our daily lives. While online posting proves very convenient for individual users, it also fosters fast-spreading o…
SANSCrypt: A Sporadic-Authentication-Based Sequential Logic Encryption Scheme
Yinghua Hu, Kaixin Yang, Shahin Nazarian +1
We propose SANSCrypt, a novel sequential logic encryption scheme to protect integrated circuits against reverse engineering. Previous sequential encryption methods focus on modifyi…
A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems
Guixiang Ma, Yao Xiao, Theodore L. Willke +3
High-level applications, such as machine learning, are evolving from simple models based on multilayer perceptrons for simple image recognition to much deeper and more complex neur…
Deep-PowerX: A Deep Learning-Based Framework for Low-Power Approximate Logic Synthesis
Ghasem Pasandi, Mackenzie Peterson, Moises Herrera +2
This paper aims at integrating three powerful techniques namely Deep Learning, Approximate Computing, and Low Power Design into a strategy to optimize logic at the synthesis level.…
Logic Verification of Ultra-Deep Pipelined Beyond-CMOS Technologies
Arash Fayyazi, Shahin Nazarian, Massoud Pedram
Traditional logical equivalence checking (LEC) which plays a major role in entire chip design process faces challenges of meeting the requirements demanded by the many emerging tec…