34 citations · 66 across the 4 of their papers we have counts for
4 papers
Local Binary Pattern Networks
Jeng-Hau Lin, Yunfan Yang, Rajesh Gupta +1
Memory and computation efficient deep learning architec- tures are crucial to continued proliferation of machine learning capabili- ties to new platforms and systems. Binarization…
Binarized Convolutional Neural Networks with Separable Filters for Efficient Hardware Acceleration
Jeng-Hau Lin, Tianwei Xing, Ritchie Zhao +4
State-of-the-art convolutional neural networks are enormously costly in both compute and memory, demanding massively parallel GPUs for execution. Such networks strain the computati…
MATEX: A Distributed Framework for Transient Simulation of Power Distribution Networks
Hao Zhuang, Shih-Hung Weng, Jeng-Hau Lin +1
We proposed MATEX, a distributed framework for transient simulation of power distribution networks (PDNs). MATEX utilizes matrix exponential kernel with Krylov subspace approximati…
Simulation Algorithms with Exponential Integration for Time-Domain Analysis of Large-Scale Power Delivery Networks
Hao Zhuang, Wenjian Yu, Shih-Hung Weng +5
We design an algorithmic framework using matrix exponentials for time-domain simulation of power delivery network (PDN). Our framework can reuse factorized matrices to simulate the…