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: Read More …

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: Read More …

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: Read More …

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. Read More …

“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]

installing OpenCV with GPU modul in Mac

I was trying to install OpenCV 2.4.5 with GPU modul in Mac OSX Mountain Lion (10.8.4) but got some errors. Trying to find solution through Google, but didn’t get much information. Finally, after couple hours, I got the idea, it’s coming from several sources, so I just collect them here to help others who may need this.

Follow instructions in OpenCV_GPU

  1. Download and extract the source.
  2. Use Terminal, and create Build folder
  3. Use CMAKE GUI to configure
  4. Use Terminal and go to Build folder, then type make to compile
  5. Type sudo make install to install

And then, you may get this error :

[ 16%] Building NVCC (Device) object modules/ ... /cuda_compile_generated_matrix_
operations.cu.o
cc1plus: error: unrecognized command line option "-Wno-narrowing"
cc1plus: error: unrecognized command line option "-Wno-delete-non-virtual-dtor"
cc1plus: error: unrecognized command line option "-Wno-unnamed-type-template-args"

Solution : Actually, it’s because in Mac use llvm-gcc compiler. So, you have to download the “TRUE” gcc compiler via MacPort. If you don’t have MacPort yet, don’t be lazy, just Google-ing how to install it. 😀 I use gcc 4.6.4, but you can try the latest one if you already have.

sudo port install gcc46

By default, anything you’ve installed via MacPort will go to /opt/local/bin/. So, you have to make a symbolic link to gcc in /usr/bin

#> sudo unlink /usr/bin/gcc
#> sudo ln -s /opt/local/bin/x86_64-apple-darwin12-gcc-4.6.4 /usr/bin/gcc

and try to compile again.


If you get error like this.

Undefined symbols for architecture x86_64:
"std::ctype<char>::_M_widen_init() const", referenced from:
stdDebugOutput(cv::String const&) in cuda_compile_generated_NCV.cu.o
ld: symbol(s) not found for architecture x86_64

Keep calm, and follow solution below. 😀

Solution : You need to set “-fno-inline” flag in CMAKE_CXX_FLAGS. Open your CMAKE GUI, put a checklist in “Advanced“, you’ll see CMAKE_CXX_FLAGS attribute name.

It should be okay, now ! 🙂

installing cuda 5 on ubuntu 12.04

  1. Download CUDA 5 installers from https://developer.nvidia.com/cuda-downloads.
  2. Add execution mode to the run file.
    • $ chmod +x cuda_5.*.run
  3. Change to terminal mode Ctrl-Alt-F1, log on and type
    • $ sudo service lightdm stop
    • $ sudo ./cuda_5.*.run
    • $ sudo shutdown -r now

If you failed to get back to login gui, type this:

  • $ sudo apt-get purge nvidia*
  • $ sudo apt-get install nvidia-current-updates-dev

errors in cuda 4.0

I’m just trying the cuda 4.0 on my macbook. And, as usual, i’m too lazy to read the “what’s new” page or doc. Just go straight to test it until got stuck with the errors.. 😀

Here, I’ll list any kind of errors i experienced with, and hopefully it’ll come along with solution.. 😛

First, i’m trying to compile an old simple code. This code was fine using cuda 3.2, but when I compile it using cuda 4.0, this kind of error comes out..

cudaLK.o:1203:53: warning: null character(s) ignored
cudaLK.o:1203:101: warning: null character(s) ignored
cudaLK.o:1203:112: warning: null character(s) preserved in literal
cudaLK.o:1203:112: warning: missing terminating ' character
cudaLK.o(1): error: unrecognized token

whoaa…… this forced me to read the programming guide, again..

Finally, when my eyes went to nvcc section, I got the clue… It looks like nvidia change the format of nvcc command.. In earlier version, simple nvcc command was

nvcc -c <cudacodefile>.cu -o <cudacodefile>.o

But for cuda 4.0, you don’t need to define the object file. nvcc will automatically define the object file based on the .cu file name. So, it should be simply..

nvcc -c <cudacodefile>.cu

to be continued later..