安裝RTX2080顯卡驅動
近日新購了一台DELL服務器，用於TensorFlow，由於顯卡是另加的，需要安裝顯卡驅動。
服務器配置
- 服務器型號：DELL PowerEdge R730
- CPU：2*Intel(R) Xeon(R) E5-2650 v4
- 內存：8*32G
- 磁盤：2*1.2T，raid 0
- 顯卡：2*Nvidia RTX2080
- 系統：Ubuntu 18.04
使用標准Ubuntu 倉庫進行自動化安裝
首先，檢測顯卡型號和推薦的驅動程序的模型。在命令行中輸入如下命令：
root@rohn-PowerEdge-R730:/home/rohn# ubuntu-drivers devices
== /sys/devices/pci0000:80/0000:80:02.0/0000:82:00.0 ==
modalias : pci:v000010DEd00001E82sv00001043sd00008674bc03sc00i00
vendor : NVIDIA Corporation
driver : nvidia-driver-410 - third-party free
driver : nvidia-driver-415 - third-party free
driver : nvidia-driver-430 - third-party free recommended
driver : nvidia-driver-418 - third-party free
driver : xserver-xorg-video-nouveau - distro free builtin
從輸出結果可以看到，目前系統已連接Nvidia RTX2080顯卡，CUDA 10.0 需要 410.x 或更高版本。並且建議安裝驅動程序是nvidia-430版本的驅動。
安裝驅動：
sudo ubuntu-drivers autoinstall
由於DELL對未認證的PCI設備的熱量估算不准確造成的，默認會加大風扇風速。可以用ipmi有關命令關閉PCIE卡的響應。
sudo apt install ipmitool
ipmitool raw 0x30 0xce 0x00 0x16 0x05 0x00 0x00 0x00 0x05 0x00 0x01 0x00 0x00
安裝完成后重啟系統：
reboot
查看：
root@rohn-PowerEdge-R730:~# nvidia-smi
Mon Jun 3 09:56:45 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.14 Driver Version: 430.14 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 2080 Off | 00000000:04:00.0 Off | N/A |
| 22% 28C P8 17W / 215W | 0MiB / 7982MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 GeForce RTX 2080 Off | 00000000:82:00.0 Off | N/A |
| 22% 29C P8 20W / 215W | 0MiB / 7982MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
安裝CUDA
# Add NVIDIA package repositories
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
sudo apt-get update
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
sudo apt install ./nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
sudo apt-get update
# Install NVIDIA driver
sudo apt-get install --no-install-recommends nvidia-driver-410
# Reboot. Check that GPUs are visible using the command: nvidia-smi
# Install development and runtime libraries (~4GB)
sudo apt-get install --no-install-recommends \
cuda-10-0 \
libcudnn7=7.4.1.5-1+cuda10.0 \
libcudnn7-dev=7.4.1.5-1+cuda10.0
# Install TensorRT. Requires that libcudnn7 is installed above.
sudo apt-get update && \
sudo apt-get install nvinfer-runtime-trt-repo-ubuntu1804-5.0.2-ga-cuda10.0 \
&& sudo apt-get update \
&& sudo apt-get install -y --no-install-recommends libnvinfer-dev=5.0.2-1+cuda10.0