24 citations · 58 across the 15 of their papers we have counts for
4 papers · 1 filter
Optimizing for In-memory Deep Learning with Emerging Memory Technology
Zhehui Wang, Tao Luo, Rick Siow Mong Goh +2
In-memory deep learning computes neural network models where they are stored, thus avoiding long distance communication between memory and computation units, resulting in considera…
DTNN: Energy-efficient Inference with Dendrite Tree Inspired Neural Networks for Edge Vision Applications
Tao Luo, Wai Teng Tang, Matthew Kay Fei Lee +3
Deep neural networks (DNN) have achieved remarkable success in computer vision (CV). However, training and inference of DNN models are both memory and computation intensive, incurr…
ThundeRiNG: Generating Multiple Independent Random Number Sequences on FPGAs
Hongshi Tan, Xinyu Chen, Yao Chen +2
In this paper, we propose ThundeRiNG, a resource-efficient and high-throughput system for generating multiple independent sequences of random numbers (MISRN) on FPGAs. Generating M…
Skew-Oblivious Data Routing for Data-Intensive Applications on FPGAs with HLS
Xinyu Chen, Hongshi Tan, Yao Chen +3
FPGAs have become emerging computing infrastructures for accelerating applications in datacenters. Meanwhile, high-level synthesis (HLS) tools have been proposed to ease the progra…