Installing CUDA 7.5 for Tesla M40 on Ubuntu 14.04.5 LTS

Install Driver

  1. Download Tesla driver (http://www.nvidia.com/Download/index.aspx?lang=en-us )
    Picture1
  2. Move to runlevel 3
    $ telinit 3
  3. Stop lightdm service
    $ service lightdm stop

  4. Change file mode of the driver package
    $ chmod +x NVIDIA-Linux-x86_64-352.99.run

Continue reading

got stuck at “Wait for Plymouth Boot Screen to Quit”

If you can’t get to the login page (booting gets stuck at “Wait for Plymouth Boot Screen to Quit”) after CUDA driver installation, then it’s probably because the kernel is trying to load xorg.conf created by NVIDIA driver. I got this experience in my laptop that has Intel + NVIDIA GPUs running CentOS 7.

Workaround Solution: Continue reading

error: “Oh no! Something has gone wrong.”


If the above message suddenly comes up in your screen after CUDA driver installation in RedHat/CentOS/Fedora OS, don’t be panic. This is happened because of xorg-x11-drv-nvidia-gl package, which is part of cuda-drivers dependencies. I got this experience in my laptop that has Intel + NVIDIA GPUs. I guess it’s because the Intel GPU is the primary GPU in my laptop, and for RedHat/CentOS/Fedora there’s no a kind of official Optimus technology, like in Windows.

Workaround Solution: Continue reading

CUDA 7.5 and Visual Studio 2015

Sorry, I won’t tell you the solution. Instead, I will show you why you should not expect for the solution of CUDA 7.5 and Visual Studio 2015 integration problem. 😀

If you try to compile a simple kernel code with nvcc and bind it with the VS2015 C++ compiler like this:

> nvcc .\kernel.cu -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\bin\x86_amd64\"

then you will get this error: Continue reading

Optimus + CUDA in Fedora 20

Recent laptops mostly come with hybrid-graphics system (two GPUs in one machine: an integrated GPU and a discrete GPU). It was first designed to control power consumption in laptops. By default, the operating system will use the integrated GPU which is less power consumption. Only when heavy activities (gaming, graphic rendering, GPU computing, etc) are performed, then operating system will move the workload to the discrete GPU.

For laptop with NVIDIA GPU, there is NVIDIA Optimus Technology for auto-switching between integrated GPU and discrete GPU. Unfortunately, NVIDIA support for this technology in Linux is not as good as in Windows. Since discrete GPU is a secondary card, installing the driver for NVIDIA GPU is not easy and may cause problem with the display manager in Linux. Continue reading

“workspace in use or cannot be created” in eclipse or nvidia nsight

– remove .lock file in workspace’s metadata folder.
rm {YourWorkspaceDir}/.metadata/.lock

– find out the RECENT_WORKSPACES attribute
cd ~/.eclipse
grep -r "RECENT_WORKSPACES" *

– once you got the file where the RECENT_WORKSPACES attribute exists, edit that file by removing the RECENT_WORKSPACES line.

[ WeekendProjects ] Python and GPU

Wiken kali ini pengen nyobain gimana menggunakan python untuk gpu programming.. ga sampe terlalu detil, cuma instalasi dan running sample codenya doank.. yang penting link-link pentingnya sudah diamankan.. [emoji grinning face with smiling eyes]

1. PyCUDA = python + cuda

Download: pypi/pycuda
Instalasi: PyCuda/Installation
Dokumentasi: documen.tician.de/pycuda/

2. PyOpenCL = python + opencl

Download: pypi/pyopencl
Instalasi: PyOpenCL/Installation
Dokumentasi: documen.tician.de/pyopencl/

Untuk sementara itu dulu.. kalau ada kesempatan dan mood, kita lanjut lagi..  [emoji grinning face with smiling eyes]