TC-GNN with Pytorch integration

Related tags

Deep Learningdeep-learningpytorchgraph-neural-networks
Overview

TC-GNN (Running Sparse GNN on Dense Tensor Core on Ampere GPU)

  • Cite this project and paper.
@inproceedings{TC-GNN,
  title={TC-GNN: Accelerating Sparse Graph Neural Network Computation Via Dense Tensor Core on GPUs},
  author={Yuke Wang and Boyuan Feng and Yufei Ding},
  booktitle={Arxiv},
  year={2022}
}
  • Clone this project.
git clone [email protected]:YukeWang96/TCGNN-Pytorch.git
  • OS & Compiler:
  • Ubuntu 16.04+
  • gcc >= 7.5
  • cmake >= 3.14
  • CUDA >= 11.0 and nvcc >= 11.0

Files and Directories.

  • config.py: the configuration file for the shape of a TC block.
  • bench.py: the benchmark file for invoking main_tcgnn.py for various datasets and models.
  • main_tcgnn.py: the main entry for running TC-GNN.
  • count_TC_blocks.py: counting the total number of TC blocks without sparse-graph translation.
  • proc_prof.py: get the detailed GPU kernel metrics from the ncu csv output.
  • TCGNN_conv/: the directory for core TC-GNN implementations, including TCGNN_kernel.cu and TCGNN.cpp.

Environment Setup.

[Method-1] Install via Docker (Recommended).

  • Go to Docker/
  • Run ./build.sh
  • Run ./launch.sh

[Method-2] Install via Conda.

  • Install conda on system Toturial.
  • Create a conda environment:
conda create -n env_name python=3.6
  • Install Pytorch:
conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c conda-forge

or using pip [Note that make sure the pip you use is the pip from current conda environment. You can check this by which pip]

pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 torchaudio==0.8.0 -f https://download.pytorch.org/whl/torch_stable.html

conda install -c dglteam dgl-cuda11.0
pip install torch requests tqdm

pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-1.8.0+cu111.html
pip install torch-sparse -f https://pytorch-geometric.com/whl/torch-1.8.0+cu111.html
pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-1.8.0+cu111.html
pip install torch-spline-conv -f https://pytorch-geometric.com/whl/torch-1.8.0+cu111.html
pip install torch-geometric

Install TC-GNN.

Go to TCGNN_conv/, then run

./build.sh

to install the TCGNN_conv modules with Pytorch binding. Note that this step is required for both Docker and Conda setup.

Download graph datasets.

Get the preprocessed datasets in .npy at here, then run

tar -zxvf tcgnn-ae-graphs.tar.gz

Running PyG baseline.

  • Go to pyg_baseline/ directory;
  • Pass the --model parameter in pyg_main.py with gcn and gin to profile the example GCN and GIN model, respectively;
  • ./0_bench.py| tee run_pyg.log to run the script and the report 10 epoch runtime for all evaluated datasets.
  • ./1_log2csv.py to convert the run_pyg.log to run_pyg.csv for ease of analysis.

Running DGL baseline.

  • Go to dgl_baseline/ directory
  • Pass the --model parameter in dgl_main.py with gcn and gin to profile the example GCN and GIN model, respectively;
  • ./0_bench.py| tee run_dgl.log to run the script and the report 10 epoch runtime for all evaluated datasets.
  • ./1_log2csv.py to convert the run_dgl.log to run_dgl.csv for ease of visualization.

Running TC-GNN.

  • Under the current project directory
  • ./0_bench.py| tee run_TCGNN.log to run the script and the report 10 epoch runtime for all evaluated datasets.
  • ./1_log2csv.py to convert the run_TCGNN.log to run_TCGNN.csv for ease of analysis.
You might also like...
🐸STT integration examples

🐸 STT 0.9.x Examples These are various examples on how to use or integrate 🐸 STT using our packages. It is a good way to just try out 🐸 STT before

coqui 92 Dec 19, 2022
Official repo for AutoInt: Automatic Integration for Fast Neural Volume Rendering in CVPR 2021
Official repo for AutoInt: Automatic Integration for Fast Neural Volume Rendering in CVPR 2021

AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021 Project Page | Video | Paper PyTorch implementation of automatic integration

Stanford Computational Imaging Lab 149 Dec 22, 2022
Hand gesture recognition based whiteboard that allows you to write on live webcam. This is the first version and has features like 4 different colors, eraser and a recording option that records your session and saves it in a "recordings" folder. Use index finger to draw and two or more fingers to move around and select items. Future version will contain more functionalities like changeable thickness, color palette, integration with zoom and google meet etc.

hand-write Hand gesture recognition based whiteboard that allows you to write on live webcam. This is the first version and has features like 4 differ

null 27 Dec 16, 2022
An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

null 45 Dec 8, 2022
Dahua Camera and Doorbell Home Assistant Integration
Dahua Camera and Doorbell Home Assistant Integration

Home Assistant Dahua Integration The Dahua Home Assistant integration allows you to integrate your Dahua cameras and doorbells in Home Assistant. It's

Ronnie 216 Dec 26, 2022
MaRS - a recursive filtering framework that allows for truly modular multi-sensor integration
MaRS - a recursive filtering framework that allows for truly modular multi-sensor integration

The Modular and Robust State-Estimation Framework, or short, MaRS, is a recursive filtering framework that allows for truly modular multi-sensor integration

Control of Networked Systems - University of Klagenfurt 143 Dec 29, 2022
ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration
ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration

ROSITA News & Updates (24/08/2021) Release the demo to perform fine-grained semantic alignments using the pretrained ROSITA model. (15/08/2021) Releas

Vision and Language Group@ MIL 48 Dec 23, 2022
Wafer Fault Detection using MlOps Integration
Wafer Fault Detection using MlOps Integration

Wafer Fault Detection using MlOps Integration This is an end to end machine learning project with MlOps integration for predicting the quality of wafe

Sethu Sai Medamallela 0 Mar 11, 2022
Official code for On Path Integration of Grid Cells: Group Representation and Isotropic Scaling (NeurIPS 2021)
Official code for On Path Integration of Grid Cells: Group Representation and Isotropic Scaling (NeurIPS 2021)

On Path Integration of Grid Cells: Group Representation and Isotropic Scaling This repo contains the official implementation for the paper On Path Int

Ruiqi Gao 39 Nov 10, 2022
Comments
  • Any docs about this project?

    Any docs about this project?

    Hi I came across this project and found the implementation is quite interesting. Is there any docs/paper that detail this project? Or you have any plan to release these kinds of information in the future?

    Thanks

    opened by mmmeee1111 1
Releases(v0.2)
Owner
YUKE WANG
https://wang-yuke.com
YUKE WANG
GitHub Repository
Learning trajectory representations using self-supervision and programmatic supervision.

Trajectory Embedding for Behavior Analysis (TREBA) Implementation from the paper: Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Y

58 Jan 06, 2023
An efficient and easy-to-use deep learning model compression framework

TinyNeuralNetwork 简体中文 TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework, which contains features like neura

Alibaba 441 Dec 25, 2022
A framework for analyzing computer vision models with simulated data

3DB: A framework for analyzing computer vision models with simulated data Paper Quickstart guide Blog post Installation Follow instructions on: https:

3DB 112 Jan 01, 2023
Minecraft Hack Detection With Python

Minecraft Hack Detection An attempt to try and use crowd sourced replays to find

Kuleen Sasse 3 Mar 26, 2022
Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers.

Less is More: Pay Less Attention in Vision Transformers Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers. By

73 Jan 01, 2023
Official repository of the AAAI'2022 paper "Contrast and Generation Make BART a Good Dialogue Emotion Recognizer"

CoG-BART Contrast and Generation Make BART a Good Dialogue Emotion Recognizer Quick Start: To run the model on test sets of four datasets, Download th

39 Dec 24, 2022
Level Based Customer Segmentation

level_based_customer_segmentation Level Based Customer Segmentation Persona Veri Seti kullanılarak müşteri segmentasyonu yapılmıştır. KOLONLAR : PRICE

Buse Yıldırım 6 Dec 21, 2021
Spatial Single-Cell Analysis Toolkit

Single-Cell Image Analysis Package Scimap is a scalable toolkit for analyzing spatial molecular data. The underlying framework is generalizable to spa

Laboratory of Systems Pharmacology @ Harvard 30 Nov 08, 2022
Orbivator AI - To Determine which features of data (measurements) are most important for diagnosing breast cancer and find out if breast cancer occurs or not.

Orbivator_AI Breast Cancer Wisconsin (Diagnostic) GOAL To Determine which features of data (measurements) are most important for diagnosing breast can

anurag kumar singh 1 Jan 02, 2022
Source Code and data for my paper titled Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chinese Question Matching

Description The source code and data for my paper titled Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chin

Zhengxiang Wang 3 Jun 28, 2022
This is the repository for paper NEEDLE: Towards Non-invertible Backdoor Attack to Deep Learning Models.

This is the repository for paper NEEDLE: Towards Non-invertible Backdoor Attack to Deep Learning Models.

1 Oct 25, 2021
Code for the paper "There is no Double-Descent in Random Forests"

Code for the paper "There is no Double-Descent in Random Forests" This repository contains the code to run the experiments for our paper called "There

2 Jan 14, 2022
YolactEdge: Real-time Instance Segmentation on the Edge

YolactEdge, the first competitive instance segmentation approach that runs on small edge devices at real-time speeds. Specifically, YolactEdge runs at up to 30.8 FPS on a Jetson AGX Xavier (and 172.7

Haotian Liu 1.1k Jan 06, 2023
Python library to receive live stream events like comments and gifts in realtime from TikTok LIVE.

TikTokLive A python library to connect to and read events from TikTok's LIVE service A python library to receive and decode livestream events such as

Isaac Kogan 277 Dec 23, 2022
🕺Full body detection and tracking

Pose-Detection 🤔 Overview Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign

Abbas Ataei 20 Nov 21, 2022
Open-sourcing the Slates Dataset for recommender systems research

FINN.no Recommender Systems Slate Dataset This repository accompany the paper "Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sa

FINN.no 48 Nov 28, 2022
an implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation using PyTorch

revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f

Simon Niklaus 59 Dec 22, 2022
DISTIL: Deep dIverSified inTeractIve Learning.

DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.

decile-team 110 Dec 06, 2022
PyTorch implementation of spectral graph ConvNets, NIPS’16

Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson

Xavier Bresson 287 Jan 04, 2023
Rethinking the Importance of Implementation Tricks in Multi-Agent Reinforcement Learning

RIIT Our open-source code for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implement and standard

405 Jan 06, 2023