Comments for Thomas

Comment on NVIDIA CUDA on Ubuntu Karmic Koala and GCC 4.4 by None

None — Mon, 19 Jul 2010 13:52:02 +0000

Interesting. The image looks exactly like http://jcuda.org/samples/Bucky01.png :D

Comment on MADALGO Summer School on GEOMETRIC DATA STRUCTURES by Milind "Milz" Bandekar

Milind "Milz" Bandekar — Sun, 18 Jul 2010 07:11:57 +0000

A New Kind of Grammars: A new kind of generative grammars that can produce the empty language is designed in this book.

http://www.amazon.com/New-Kind-Grammars-generative-grammars/dp/1452828687

An unrepresented mongrel of Computer Science, the null or invalid string gets a new representative symbol in this book.

Comment on NVIDIA CUDA on Ubuntu Karmic Koala and GCC 4.4 by Dean Wood

Dean Wood — Fri, 18 Jun 2010 19:11:54 +0000

Hi,

I am having the same problem as Davi so if either of you have any idea that would be cool.

Thanks

Dean

Comment on NVIDIA CUDA on Ubuntu Karmic Koala and GCC 4.4 by Davi

Davi — Tue, 01 Jun 2010 18:11:57 +0000

Hey Thomas,
I am tryig to install the SDK examples. I already downgraded the gcc and g++ to 4.3. When I try to make, it cannot find -lGL. How should I do to install this library?

Comment on NVIDIA CUDA on Ubuntu Karmic Koala and GCC 4.4 by jacksparrow

jacksparrow — Sat, 29 May 2010 12:19:08 +0000

hi ,
I run through all your instruction …but when i run deviceQuery command then got the following error:-
bash: ./deviceQuery: No such file or directory

Please help me get out of this as i have spent so much time on installing CUDA on my ubuntu9.04 machine

Comment on Tutorials in PDF: Matrix Algrebra by yekani

yekani — Sun, 25 Apr 2010 20:15:59 +0000

YASSIN :I need some book about matrices

Comment on NVIDIA CUDA on Ubuntu Karmic Koala and GCC 4.4 by Tobbe

Tobbe — Tue, 20 Apr 2010 07:41:51 +0000

Hi! Thank you very much!
I got stuck because I only had g++ 4.4, but your instructions made my day!
Now I’m excited in a disturbing way!! :D

Comment on Sony VAIO SZ6 and Ubuntu by JoshSN

JoshSN — Sat, 03 Apr 2010 02:32:30 +0000

I guess I never really used the speed/stamina switch or something, and only recently learned that it switched graphics chips. Now I want it to work, but I guess it is broken. With the switch in either position lspci never lists nVidia.

Is there a way other than the switch to get speed mode?

Comment on Graphics Engine by dev

dev — Mon, 29 Mar 2010 12:47:12 +0000

how can i download it?

Comment on NVIDIA CUDA on Ubuntu Karmic Koala and GCC 4.4 by Marxwing

Marxwing — Thu, 18 Mar 2010 17:08:20 +0000

Sorry, was my mistake. But now I think of a problem…

marxwing@marxwing-laptop:~/NVIDIA_GPU_Computing_SDK/C$ bin/linux/release/deviceQuery
CUDA Device Query (Runtime API) version (CUDART static linking)
There is no device supporting CUDA.

Device 0: “Device Emulation (CPU)”
CUDA Driver Version: 2.30
CUDA Runtime Version: 2.30
CUDA Capability Major revision number: 9999
CUDA Capability Minor revision number: 9999
Total amount of global memory: 4294967295 bytes
Number of multiprocessors: 16
Number of cores: 128
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 16384 bytes
Total number of registers available per block: 8192
Warp size: 1
Maximum number of threads per block: 512
Maximum sizes of each dimension of a block: 512 x 512 x 64
Maximum sizes of each dimension of a grid: 65535 x 65535 x 1
Maximum memory pitch: 262144 bytes
Texture alignment: 256 bytes
Clock rate: 1.35 GHz
Concurrent copy and execution: No
Run time limit on kernels: No
Integrated: Yes
Support host page-locked memory mapping: Yes
Compute mode: Default (multiple host threads can use this device simultaneously)

Test PASSED

Press ENTER to exit…

marxwing@marxwing-laptop:~/NVIDIA_GPU_Computing_SDK/C$ bin/linux/release/volumeRender
[ CUDA 3D Volume Render ]
NVIDIA: could not open the device file /dev/nvidiactl (Permission denied).
freeglut (bin/linux/release/volumeRender): Unable to create direct context rendering for window ‘CUDA volume rendering’
This may hurt performance.

CUDA Capability Major revision number: 9999 , CUDA Capability Minor revision number: 9999 , Warp size: 1, Run time limit on kernels: No …these characteristics are different … would greatly appreciate any help you can provide