I won't talk about the installation of cuda and optimus on the theme. I found that some foreigners did not succeed or there were few articles about Kali. After more than one day of repeated installation and testing, this article is the final one, the English version is also released.
InstallCudaAndNvidiaDriver
This step is relatively simple. Before installation, we recommend that you edit the/etc/apt/source. list file, comment out the foreign source and switch it to the Chinese Emy of science and technology, and download it quickly. The address of KE dayuan is as follows:
| Deb http://mirrors.ustc.edu.cn/kali kali main non-free contrib |
| Deb-src http://mirrors.ustc.edu.cn/kali kali main non-free contrib |
| Deb http://mirrors.ustc.edu.cn/kali-security kali/updates main contrib non-free |
Run the following command to install
| Apt-get install nvidia-detect nvidia-libopencl1 nvidia-opencl-common nvidia-support nvidia-opencl-icd nvidia-visual-profiler nvidia-glx nvidia-installer-cleanup nvidia-kernel-common nvidia -smi nvidia-alternative nvidia-opencl-dev libglx-nvidia-alternatives nvidia-kernel-dkms nvidia-cuda-toolkit nvidia-vdpau-driver nvidia-xconfig glx-alternative-nvidia libgl1-nvidia-alternatives nvidia -settings libgl1-nvidia-glx xserver-xorg-video-nvidia unzip libcudart4 libcufft4 libnpp4 libnvidia-compiler libcuda1 runtime libnvidia-ml1 unzip libcusparse4 libcurand4 python-pycuda-doc python-pycuda-headers python-pycuda nvidia-cuda- doc nvidia-cuda-gdb |
Because many packages may be a little slow, the installation process will pop up two windows to confirm, just OK. After the execution, the toolkit and driver are installed, and then some variables are written to the system, in/root /. add the following paragraph to the end of bashrc:
| PATH = $ PATH:/usr/lib/nvidia-cuda-toolkit/bin |
| LD_LIBRARY_PATH = $ LD_LIBRARY_PATH:/usr/lib/nvidia-cuda-toolkit/lib:/lib |
| Export PATH |
| Export LD_LIBRARY_PATH |
You can execute ldconfig to take effect immediately, but it will be restarted once.
Install
Pyrit-cuda
Next, recompile A pyrit to try GPU. The download address of pyrit is:
Https://code.google.com/p/pyrit/downloads/list
Download pyrit-0.4.0.tar.gzand cpyrit-cuda-0.4.0.tar.gz. After the download, install the required tool.
| Atp-get install libpcap-dev python2.7-dev |
Decompress pyrit-0.4.0.tar.gz and install
| Tar-xzvf pyrit-0.4.0.tar.gz |
| Cd pyrit-0.4.0 |
| Python setup. py build |
| Python setup. py install |
Decompress cpyrit-cuda-0.4.0.tar.gz
| Tar-xzvf cpyrit-cuda-0.4.0.tar.gz |
| Cd cpyrit-cuda-0.4.0 |
Here we need to make some changes, edit setup. py, and set the 35th rows
| For path in ('/usr/local/cuda', '/opt/cuda '): |
Change
| For path in ('/usr/local/cuda', '/usr/lib/nvidia-cuda-toolkit', '/opt/cuda '): |
Otherwise the installation program cannot find nvcc
Then install
| Python setup. py build |
| Python setup. py install |
After installation, run
We should be able to see the GPU.
| #1: 'cuda-Device #1 'geforce 8400 gs'' |
| #2: 'cpu-Core (SSE2 )' |
| #3: 'cpu-Core (SSE2 )' |
| #4: 'cpu-Core (SSE2 )' |
| #5: 'cpu-Core (SSE2 )' |
| #6: 'cpu-Core (SSE2 )' |
| #7: 'cpu-Core (SSE2 )' |
| #8: 'cpu-Core (SSE2 )' |
Install
Optimus
Retrieve the source Key
| Wget-O-http://suwako.nomanga.net/suwako.asc | apt-key add- |
Add the Bumblebee source to/etc/apt/source. list.
| Deb http://suwako.nomanga.net/debian sid main contrib |
| Deb-src http://suwako.nomanga.net/debian sid main |
Then execute the installation
| Apt-get update |
| Apt-get install bumblebee-nvidia |
After installation, add root to the bemblebe group and restart
After restart, you can test and run them separately.
| Glxspheres |
| Optirun glxspheres |
The number of frames is different.
