GATECH-EIC/ShiftAddNet

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66
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Language
Python
License
MIT License
Created almost 4 years ago
Updated almost 4 years ago

GATECH-EIC/ShiftAddNet

GATECH-EIC

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[NeurIPS 2020] ShiftAddNet: A Hardware-Inspired Deep Network

Early-Bird-Tickets

[ICLR 2020] Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks

HW-NAS-Bench

[ICLR 2021] HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark

ViTCoD

[HPCA 2023] ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design

AutoDNNchip

BNS-GCN

[MLSys 2022] "BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling" by Cheng Wan, Youjie Li, Ang Li, Nam Sung Kim, Yingyan Lin

ShiftAddLLM

ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization

DepthShrinker

[ICML 2022] "DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks", by Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin

GCoD

[HPCA 2022] GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design

CPT

[ICLR 2021] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin

ShiftAddViT

[NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer

PipeGCN

[ICLR 2022] "PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication" by Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin

Patch-Fool

[ICLR 2022] "Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?" by Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin

Castling-ViT

[CVPR 2023] Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference

DNN-Chip-Predictor

[ICASSP'20] DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures

E2Train

[NeurIPS 2019] E2-Train: Training State-of-the-art CNNs with Over 80% Less Energy

ViTALiTy

ViTALiTy (HPCA'23) Code Repository

SuperTickets

[ECCV 2022] SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning

ShiftAddNAS

[ICML 2022] ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks

mg-verilog

Auto-NBA

[ICML 2021] "Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators" by Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan Lin

NeRFool

[ICML 2023] "NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations" by Yonggan Fu, Ye Yuan, Souvik Kundu, Shang Wu, Shunyao Zhang, Yingyan (Celine) Lin

S3-Router

[NeurIPS 2022] "Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing" by Yonggan Fu, Yang Zhang, Kaizhi Qian, Zhifan Ye, Zhongzhi Yu, Cheng-I Lai, Yingyan Lin

Robust-Scratch-Ticket

[NeurIPS 2021] "Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks" by Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David Cox, Yingyan Lin

Double-Win-Quant

[ICML 2021] "Double-Win Quant: Aggressively Winning Robustness of Quantized DeepNeural Networks via Random Precision Training and Inference" by Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin

Linearized-LLM

[ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

LLM4HWDesign_Starting_Toolkit

LLM4HWDesign Starting Toolkit

FracTrain

[NeurIPS 2020] "FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training" by Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin

torchshiftadd

An open-sourced PyTorch library for developing energy efficient multiplication-less models and applications.

HALO

The official code for [ECCV2020] "HALO: Hardware-aware Learning to Optimize"

NASA

[ICCAD 2022] NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks

SACoD

[ICCV 2021] "SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam" by Yonggan Fu, Yang Zhang, Yue Wang, Zhihan Lu, Vivek Boominathan, Ashok Veeraraghavan, Yingyan Lin

Edge-LLM

[DAC 2024] EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting

TinyML-Contest-Solution

TinyML2023EIC-Gatech-Open

ACT

[ICML 2024] Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration

Early-Bird-GCN

[AAAI 2022] Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets

Hint-Aug

EyeCoD

[ISCA 2022] EyeCoD: Eye Tracking System Acceleration via FlatCam-based Algorithm & Accelerator Co-Design

InstantNet

[DAC 2021] "InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks" by Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yifan Jiang, Chaojian Li, Yongyuan Liang, Mingchao Jiang, Zhangyang Wang, Yingyan Lin

Spline-EB

[TMLR] Max-Affine Spline Insights Into Deep Network Pruning