using rsync to copy files and folders

Quest for a tool to do a copy excluding hidden files lead me to find the rsync command. Here is how I copy a folder from source to destination excluding all hidden files/folders (all that with a "." prefix in the name).

rsync -a --exclude='.*' source/ destination/

This might be especially useful when copying folders checked out from SVN, that needs to be checked-in to a different location. Having the .svn folder under sub-folders can cause them not to be checked in.

Read more...

svn - 1

To get the list of all modified files, after a specific REVNO to the latest HEAD

svn diff -r REVNO:HEAD --summarize

Read more...

Downloading an MMS stream with mencoder

All you need is one command:

mencoder mms://url/filename.wmv -ovc copy -oac copy -o output.wmv

Read more...

getting ~/.bashrc to be executed

If your ~/.bashrc is not getting executed every time you login, add these lines to your ~/.bash_profile file:

 # include .bashrc if it exists 
if [ -f ~/.bashrc ]; then 
  source ~/.bashrc 
fi 

Read more...

CUDA 3.0 and gcc 4.4.x

Deadly combination! Compilation breaks when you try to do make on NVidia SDK example projects even. Problem is with nvcc incompatibility. A gcc version of 4.3.x works fine (as of this date).

Here is the compilation error listing:

/usr/include/string.h:43: error: inline function ‘void* memcpy(void*, const void*, size_t)’ cannot be declared weak

/usr/include/string.h:64: error: inline function ‘void* memset(void*, int, size_t)’ cannot be declared weak

/usr/include/bits/string3.h:49: error: inline function ‘void* memcpy(void*, const void*, size_t)’ cannot be declared weak

/usr/include/bits/string3.h:78: error: inline function ‘void* memset(void*, int, size_t)’ cannot be declared weak

/usr/local/cuda/bin/../include/common_functions.h:59: error: inline function ‘void* memset(void*, int, size_t)’ cannot be declared weak

/usr/local/cuda/bin/../include/common_functions.h:62: error: inline function ‘void* memcpy(void*, const void*, size_t)’ cannot be declared weak

/usr/local/cuda/bin/../include/math_functions.h:422: error: inline function ‘int __signbit(double)’ cannot be declared weak

/usr/local/cuda/bin/../include/math_functions.h:427: error: inline function ‘int __signbitf(float)’ cannot be declared weak

/usr/local/cuda/bin/../include/math_functions.h:440: error: inline function ‘int __signbitl(long double)’ cannot be declared weak

/usr/include/bits/mathcalls.h:350: error: inline function ‘int __signbit(double)’ cannot be declared weak

/usr/include/bits/mathcalls.h:350: error: inline function ‘int __signbitf(float)’ cannot be declared weak

/usr/include/bits/mathcalls.h:350: error: inline function ‘int __signbitl(long double)’ cannot be declared weak

/usr/include/bits/mathinline.h:38: error: inline function ‘int __signbitf(float)’ cannot be declared weak

/usr/include/bits/mathinline.h:50: error: inline function ‘int __signbit(double)’ cannot be declared weak

/usr/include/bits/mathinline.h:62: error: inline function ‘int __signbitl(long double)’ cannot be declared weak

/usr/include/c++/4.4/i486-linux-gnu/bits/c++locale.h: In function ‘int std::__convert_from_v(__locale_struct* const&, char*, int, const char*, ...)’:

/usr/include/c++/4.4/i486-linux-gnu/bits/c++locale.h:86: error: ‘__builtin_stdarg_start’ was not declared in this scope

dxtc.cu: In function ‘int main(int, char**)’:

dxtc.cu:789: warning: ignoring return value of ‘size_t fread(void*, size_t, size_t, FILE*)’, declared with attribute warn_unused_result

make[1]: *** [obj/i386/release/dxtc.cu.o] Error 1

Fixing the error basically means commenting out the specific lines in math_functions.h and common_functions.h on which the compiler shows the error (shown in dark blue).

Solution: comment them out. This will fix compilation errors. I have not tested the side-effect of this hack. But as for fixing compilation break, it works!

Note:

I needed a few more steps:

1. Uninstall gcc-4.4.x, g++-4.4.x (and all 4.4.x libraries)

2. Install gcc and g++ 4.3.x versions.

3. ln -s /usr/bin/gcc-4.3. /usr/bin/gcc

4. ln -s /usr/bin/g++-4.3. /usr/bin/g++

5. Install libXi-dev (since -lXi failed)

6. Install libxmu-dev (since -lxmu failed)

Steps 5,6 were required when I tried to build GL applications like fluidGL, simpleGL etc.

Related links:

http://www.piotrkrzyzek.com/nvidia-cuda-sdk-gcc-4-4-problems-solved-in-kubuntu-jaunt-910-usrbinld-cannot-find-lglut-and-__signbit__signbitf__signbitl__signbitd-cannot-be-declared-weak/

http://forums.nvidia.com/index.php?showtopic=83217

http://forums.nvidia.com/index.php?showtopic=87692

Read more...

Installing CUDA on Ubuntu

Its simple as counting 1, 2, 3.. (as long as everything is supported and works fine).

PART I:
NVidia (developer) driver that is required by CUDA (as mentioned in the GPU computing page). This might be different from the latest driver you might find in other pages.

Step 1: Download the driver for your nvidia graphics card. These will come as .run files.

Step 2: If you have traces of your (now obsolete) driver from nVidia, get rid of them with the following 2 commands:
sudo apt-get remove --purge nvidia
sudo nvidia-installer --uninstall

Step 3: Stop your display manager
sudo /etc/init.d/gdm stop

Step 3.5: Now you do not have your X running, so switch to console:
ctrl + alt + F1

Step 4:
sudo sh devdriver_3.2_linux_32_260.24.run

This should bring up a console based miniature GUI, enter details as required. And complete the installation.

Step 5: Bring back the X
sudo /etc/init.d/gdm start


PART II: Installing CUDA toolkit
Step 1: Download the CUDA toolkit (cudatoolkit_3.2.9_linux_32_ubuntu10.04.run) from GPU Computing page at NVidia site.

Step 2: Run the file:
sh cudatoolkit_3.2.9_linux_32_ubuntu10.04.run

Make sure you do not do it as root (or with sudo prefix).
Step 3: I prefer leaving the default locations for installation.

Step 4: Assuming default locations of installation, set environment variables

export PATH=/usr/local/cuda/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib


PART III: Installing sample projects, SDK etc.

Step 1: Download gpucomputingsdk_3.2_linux.run

Step 2: Run (do not run this in root mode)
sh gpucomputingsdk_3.2_linux.run

Step 3: Give default locations to CUDA installation (or the modified locations, if you have modified them)

Step 4: Test if its fine
cd ~/NVIDIA_GPU_Computing_SDK/C
make

This should build all example projects included in the SDK without any error. If that goes fine, it means you have a working CUDA environment to work with.

Now try running one of the programs (one I like is to query the GPU)
cd bin/linux/release/
./deviceQuery

It gives me an output like this:
./deviceQuery Starting...

CUDA Device Query (Runtime API) version (CUDART static linking)

There is 1 device supporting CUDA

Device 0: "GeForce GT 240M"
CUDA Driver Version: 3.20
CUDA Runtime Version: 3.20
. . . . .
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 3.20, CUDA Runtime Version = 3.20, NumDevs = 1, Device = GeForce GT 240M



Components that I have/chose:

1. Ubtuntu 10.04 (32bit)
   
2. NVidia GT240M graphics card
3. devdriver_3.2_linux_32_260.24.run driver
4. cudatoolkit_3.2.9_linux_32_ubuntu10.04.run
5. gpucomputingsdk_3.2_linux.run
   

Read more...

less and vim

When you are "lessing" a file, just type :gv to open the file in vim for editing. Upon quitting vim, it will return back to the less-view.

Read more...

opengl capturing using GLC

GLC is a tool that allows recording of opengl renderings done by applications.

Capture
glc-capture -s -o ~/output1.glc ./assignment

Play
glc-play ~/output.glc -y 1 -o - | mplayer -demuxer y4m -

Read more...