配置 NVIDIA DeepStream SDK on Tesla V2.0
NVIDIA DeepStream SDK on Tesla V2.0的环境要求为：
Ubuntu 16.04
CUDA 9.2
官方安装指导为：https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html
在命令行中应做如下选择：（由于已经安装了不同版本的cuda，并没有选择直接生成软链接。）
Do you accept the previously read EULA?
accept/decline/quit: accept
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 396.26?
(y)es/(n)o/(q)uit: n
Install the CUDA 9.2 Toolkit?
(y)es/(n)o/(q)uit: y
Enter Toolkit Location
[ default is /usr/local/cuda-9.2 ]:
Do you want to install a symbolic link at /usr/local/cuda?
(y)es/(n)o/(q)uit: n
Install the CUDA 9.2 Samples?
(y)es/(n)o/(q)uit: y
Enter CUDA Samples Location
[ default is /home/deepstream ]:
Installing the CUDA Toolkit in /usr/local/cuda-9.2 ...
Missing recommended library: libXmu.so
Installing the CUDA Samples in /home/deepstream ...
Copying samples to /home/deepstream/NVIDIA_CUDA-9.2_Samples now...
Finished copying samples.
===========
= Summary =
===========
Driver: Not Selected
Toolkit: Installed in /usr/local/cuda-9.2
Samples: Installed in /home/deepstream, but missing recommended libraries
Please make sure that
- PATH includes /usr/local/cuda-9.2/bin
- LD_LIBRARY_PATH includes /usr/local/cuda-9.2/lib64, or, add /usr/local/cuda-9.2/lib64 to /etc/ld.so.conf and run ldconfig as root
To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-9.2/bin
Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-9.2/doc/pdf for detailed information on setting up CUDA.
***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 384.00 is required for CUDA 9.2 functionality to work.
To install the driver using this installer, run the following command, replacing
with the name of this run file: sudo
.run -silent -driver 然后sudo vim .bashrc，按照提示：
- PATH includes /usr/local/cuda-9.2/bin
- LD_LIBRARY_PATH includes /usr/local/cuda-9.2/lib64
再source .bashrc完成更新。如果nvcc --version则可以看到安装成功：
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Wed_Apr_11_23:16:29_CDT_2018
Cuda compilation tools, release 9.2, V9.2.88
TENSORT 4.0
注意需要cuDNN 7.1.3 环境，但是官网上我只找到有7.1.2和7.1.4？那就赌一把7.1.4向下兼容吧
我选择了：
Download cuDNN v7.1.4 (May 16, 2018), for CUDA 9.2cuDNN v7.1.4 Library for Linux
在官网https://developer.nvidia.com/nvidia-tensorrt-download 上下载tar包，然后
tar -xf TensorRT-4.0.1.6.Ubuntu-16.04.4.x86_64-gnu.cuda-9.2.cudnn7.1.tar
vim ~/.bashrc
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/TensorRT-4.0.1.6/lib
source ~/.bashrc~/TensorRT-4.0.1.6/python$ sudo pip2 install tensorrt-4.0.1.6-cp27-cp27mu-linux_x86_64.whl
随后安装Python UFF package
~/TensorRT-4.0.1.6/uff$ sudo pip2 install uff-0.4.0-py2.py3-none-any.whl
再安装Python graphsurgeon package
~/TensorRT-4.0.1.6/graphsurgeon$ sudo pip2 install graphsurgeon-0.2.0-py2.py3-none-any.whl
OpenCV 3.4.x
Gstreamer 1.8.3
sudo apt-get install libgstreamer1.0-0 gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav gstreamer1.0-doc gstreamer1.0-tools
如果出现错误：dpkg: error processing package initramfs-tools (--configure):
subprocess installed post-installation script returned error exit status 1
Errors were encountered while processing:
initramfs-tools的错误，不要慌，执行：
sudo rm -f /var/lib/dpkg/info/initramfs-tools.post*
sudo rm -f /var/lib/dpkg/info/initramfs-tools.pre*
sudo rm -f /var/lib/dpkg/info/bcmwl-kernel-source.post*
sudo rm -f /var/lib/dpkg/info/bcmwl-kernel-source.pre*
sudo dpkg --configure -a
NVIDIA driver396+
sudo apt install nvidia-396
如果出现Failed to initialize NVML: Driver/library version mismatch，不要慌，重启即可。
（未完待续）