Ubuntu-Linux.txt

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wi-fi 잡기 ( Ubuntu 설치시 기본으로 잡을 수 있지만 바꿔야하는 경우 )
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ip a 로 wifi 드라이버 확인

sudo vim /etc/netplan/~.yaml 아래 템플릿처럼 설정

network:
  version: 2
  wifis:
    wlp129s0f0:
      dhcp4: true
      access-points:
        "{WI-FI Name}":
          auth:
            key-management: "psk"
            password: "****"
        "{WI-FI Name}":
          auth:
            key-management: "psk"
            password: "****"

sudo netplan apply
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Ubuntu 24.04용 HWE 커널 업데이트
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sudo apt install -y linux-generic-hwe-24.04
sudo reboot

uname -r ( 6.x.x 계열이면 정상 )

ip a 로 LAN 드라이버 확인 

sudo vim /etc/netplan/~.yaml 아래 템플릿처럼 설정

network:
  ethernets:
    enp130s0:
      dhcp4: false
      addresses:
        - {IP}/24
      routes:
        - to: default
          via: {GW}
      nameservers:
        addresses:
          - 8.8.8.8
          - 8.8.4.4

sudo netplan apply
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파티션 확장
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sudo vgdisplay ubuntu-vg 

sudo lvextend -l +100%FREE /dev/ubuntu-vg/ubuntu-lv 

sudo resize2fs /dev/ubuntu-vg/ubuntu-lv 

df -h /
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SSH Server 설치
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sudo apt update
sudo apt install -y openssh-server

systemctl status ssh

sudo systemctl enable ssh
sudo systemctl start ssh

ip a
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노트북 닫은 상태로 서버 가동
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sudo vim /etc/systemd/logind.conf

HandleLidSwitch=ignore
HandleLidSwitchDocked=ignore
HandleSuspendKey=ignore
HandleHibernateKey=ignore

sudo systemctl restart systemd-logind
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서버 시간 변경
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timedatectl

sudo timedatectl set-timezone Asia/Seoul

date
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GPU Setting
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1. nvidia 드라이버 설치

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update

ubuntu-drivers devices

sudo ubuntu-drivers autoinstall

2. GPU 확인

- nvidia-smi > GeForce RTX 5090 확인

- https://ko.wikipedia.org/wiki/CUDA

- 자신의 GPU에 맞는 컴퓨팅 기능 확인 ( 12.0 )

- 컴퓨팅 기능에 맞는 CUDA SDK 버전 확인 ( 12.8 ~ )

3. CUDA 설치

https://developer.nvidia.com/cuda-toolkit-archive

12.9.0 버전 wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-keyring_1.1-1_all.deb

sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install cuda-toolkit-12-9

# 접속 후 아래 코드 추가
vim ~/.bashrc 

#아래의 두 문장을 맨 끝에 입력 후, 저장
export PATH=/usr/local/cuda-12.9/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-12.9/lib64:$LD_LIBRARY_PATH

# bashrc파일 수정 후, 적용
source ~/.bashrc
#CUDA 버전을 바꾸고싶은경우 bashrc만 수정해주면 됨

# CUDA 설치 확인
nvcc --version

4. cuDNN 설치

https://developer.nvidia.com/rdp/cudnn-archive

맞는 쿠다버전의 최신 cudnn 선택 ( Linux 용 Tar파일 ) 후 다은로드 ( 회원가입 인증이 필요하므로 wget 사용 불가 )

/home/wjhjs/installers 폴더안에 다운로드된 파일 옮겨놓기 ( 로컬에서 받아서 서버로 전송 )

tar -xvf cudnn-linux-x86_64-8.9.7.29_cuda12-archive.tar.xz
sudo cp cudnn-linux-x86_64-8.9.7.29_cuda12-archive/include/cudnn*.h /usr/local/cuda-12.9/include
sudo cp -P cudnn-linux-x86_64-8.9.7.29_cuda12-archive/lib/libcudnn* /usr/local/cuda-12.9/lib64
sudo chmod a+r /usr/local/cuda-12.9/lib64/libcudnn*

# cuDNN 설치 확인
cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

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재부팅시 vllm 자동 서빙
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sudo vim /etc/systemd/system/vllm.service

[Unit]
Description=vLLM OpenAI Compatible Server (gpt-oss-20b)
After=network.target

[Service]
Type=simple
User=axtft

Environment=HF_HOME=/home/axtft/.cache/huggingface
Environment=CUDA_VISIBLE_DEVICES=0

ExecStart=/home/axtft/anaconda3/envs/axtft/bin/vllm serve \
  /home/axtft/projects/axtft/models/gpt-oss-20b \
  --served-model-name gpt-oss-20b \
  --max-model-len 8192 \
  --gpu-memory-utilization 0.9 \
  --host 0.0.0.0 \
  --port 8000

Restart=always
RestartSec=5
LimitNOFILE=65535

[Install]
WantedBy=multi-user.target

sudo systemctl daemon-reload
sudo systemctl enable vllm.service
sudo systemctl start vllm.service

systemctl list-timers | grep vllm

특정 시간대에 vllm 서빙 재시작

sudo vim /etc/systemd/system/vllm-restart.service

[Unit]
Description=Restart vLLM service

[Service]
Type=oneshot
ExecStart=/bin/bash -c "systemctl stop vllm.service && sleep 10 && systemctl start vllm.service"

sudo vim /etc/systemd/system/vllm-restart.timer

[Unit]
Description=Daily restart of vLLM service

[Timer]
OnCalendar=*-*-* 06:00:00
Persistent=true

[Install]
WantedBy=timers.target

sudo systemctl daemon-reload
sudo systemctl enable vllm-restart.timer
sudo systemctl start vllm-restart.timer

systemctl list-timers | grep vllm
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redis 설치
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sudo apt install redis-server -y
sudo systemctl enable redis-server
sudo systemctl start redis-server

sudo vim /etc/redis/redis.conf

( 외부와 통신시, 내부 통신으로 하는것이 맞음 )

bind 0.0.0.0 ( 127.0.0.1 10.100.100.100 )
protected-mode no ( yes )
requirepass strongpassword

sudo systemctl restart redis-server
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파일 전송
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- 기본 압축
zip -r folder_name.zip folder_name/

- 비밀번호 설정
zip -r -e secure.zip folder_name/

- 원격 -> 로컬
scp user@linux-server-ip:/home/user/my_data.zip .

python -m http.server 8080

- 로컬 -> 원격
scp C:\Users\you\Downloads\my_data.zip user@linux-server-ip:/home/user/