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09/21/2023
SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices
Adiabatic Quantum-Flux-Parametron (AQFP) is a superconducting logic with...
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11/15/2022
HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers
While vision transformers (ViTs) have continuously achieved new mileston...
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09/18/2022
StereoVoxelNet: Real-Time Obstacle Detection Based on Occupancy Voxels from a Stereo Camera Using Deep Neural Networks
Obstacle detection is a safety-critical problem in robot navigation, whe...
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07/08/2022
FAIVConf: Face enhancement for AI-based Video Conference with Low Bit-rate
Recently, high-quality video conferencing with fewer transmission bits h...
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02/10/2022
F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization
Neural network quantization is a promising compression technique to redu...
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06/16/2021
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI
Recent research demonstrated the promise of using resistive random acces...
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06/16/2021
FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator
Recent works demonstrated the promise of using resistive random access m...
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09/17/2020
Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning
Pretrained large-scale language models have increasingly demonstrated hi...
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07/20/2020
Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
Mobile devices are becoming an important carrier for deep learning tasks...
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03/13/2020
A Privacy-Preserving DNN Pruning and Mobile Acceleration Framework
To facilitate the deployment of deep neural networks (DNNs) on resource-...
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02/19/2020
RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition
Recurrent neural networks (RNNs) based automatic speech recognition has ...
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01/23/2020
SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency
Structured weight pruning is a representative model compression techniqu...
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01/23/2020
BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method
Accelerating DNN execution on various resource-limited computing platfor...
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11/24/2019
A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation
The computing wall and data movement challenges of deep neural networks ...
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07/03/2019
Non-structured DNN Weight Pruning Considered Harmful
Large deep neural network (DNN) models pose the key challenge to energy ...
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04/30/2019
ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning
The state-of-art DNN structures involve high computation and great deman...
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03/23/2019
