Google Cloud Platform(GCP, GCE)에 cuda, cuDNN, conda 설치

1. CUDA 및 cuDNN 설치

GCE 사양

region: asia-northeast3-b  
GPU: Nvidia-T4, num:1  
CPU: n1-standard-4(vCPU 4개, 15GB 메모리)
Boot-disk: Ubuntu20.04LTS at least 30GB
Firewall: allow all

nvidia driver 및 cuda 설치

sudo apt install ubuntu-drivers-common -y  
sudo apt install nvidia-driver-515 -y  
wget https://developer.download.nvidia.com/compute/cuda/11.7.0/local_installers/cuda_11.7.0_515.43.04_linux.run

환경 변수 설정

export PATH=/usr/local/cuda-11.7/bin${PATH:+:${PATH}}  
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

source ~/.bashrc

# 설치 확인
nvcc --version

cudnn 설치

https://developer.nvidia.com/cudnn

CUDA Deep Neural Network

cuda에 맞는 cudnn 다운로드 후 gce 폴더에 넣고 압축 풀기

tar -xvf cudnn-linux-x86_64-8.5.0.96_cuda11-archive.tar.xz

sudo cp cudnn-linux-x86_64-8.5.0.96_cuda11-archive/include/cudnn*.h /usr/local/cuda/include
sudo cp -P cudnn-linux-x86_64-8.5.0.96_cuda11-archive/lib/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*

cudnn 설치 확인

cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

gce 껏다 다시 키기

sudo reboot

2. conda 설치

conda 다운로드(miniconda 해도 됨)

wget https://repo.anaconda.com/archive/Anaconda3-2020.07-Linux-x86_64.sh

conda 설치

bash Anaconda3-2020.07-Linux-x86_64.sh

source ~/.bashrc

가상환경 만들기

conda create -n final python=3.9.7
conda activate final

프로젝트 repository clone하기

git clone https://github.com/boostcampaitech5/level3_cv_finalproject-cv-11.git

requirements 설치하기

pip install -r requirements.txt