200 citations · 520 across the 13 of their papers we have counts for
3 papers · 1 filter
High-Throughput In-Memory Computing for Binary Deep Neural Networks with Monolithically Integrated RRAM and 90nm CMOS
Shihui Yin, Xiaoyu Sun, Shimeng Yu +1
Deep learning hardware designs have been bottlenecked by conventional memories such as SRAM due to density, leakage and parallel computing challenges. Resistive devices can address…
Automatic Compiler Based FPGA Accelerator for CNN Training
Shreyas Kolala Venkataramanaiah, Yufei Ma, Shihui Yin +4
Training of convolutional neural networks (CNNs)on embedded platforms to support on-device learning is earning vital importance in recent days. Designing flexible training hard-war…
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen +3
The computational demands of computer vision tasks based on state-of-the-art Convolutional Neural Network (CNN) image classification far exceed the energy budgets of mobile devices…