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NVIDIA CUDA-based bilinear (2D) interpolation

15 Apr 2009 (Updated 30 Jun 2009)

Incredible speed boost in comparison to the Matlab implementation. (interp2)

File Information
Description	This code was inspired by Alexander Huth's bilinear interpolation approach ( http://www.mathworks.com/matlabcentral/fileexchange/20248 ) also using the GPU's built-in bilinear texture interpolation capability, which is indeed very fast. The speedup is depending on your CUDA enabled graphics hardware. The more multiprocessors, texture units, ... the better the results will be. In comparison to Alexander's cudainterp2, I added some performance improvements and the capability to interpolate complex numbers too. Feel free to write some feedback or a comment.
Acknowledgements	The author wishes to acknowledge the following in the creation of this submission: 2D CUDA-based bilinear interpolation
MATLAB release	MATLAB 7.6 (R2008a)
Other requirements	CUDA enabled graphics hardware, NVIDIA CUDA Toolkit, NVIDIA CUDA SDK, only tested with Windows (XP,Vista)
Zip File Content
Other Files	bilininterp/bilininterp.cu, bilininterp/bilininterp.m, bilininterp/bilininterp_complex_test.m, bilininterp/bilininterp_defines.h, bilininterp/bilininterp_kernel.cu, bilininterp/bilininterp_speed_test.m, bilininterp/bilininterp_trajectory_test.m, bilininterp/bin/nvmex.pl, bilininterp/build_mex.m, bilininterp/cudainterp2/cudainterp2.cu, bilininterp/cudainterp2/cudainterp2.m, bilininterp/cudainterp2/README, bilininterp/cudainterp2/testcudainterp2.m, bilininterp/nvmex.m, bilininterp/nvmex_helper.m, bilininterp/nvmexopts_r2008a.bat, bilininterp/README, bilininterp/test_bilininterp_vs_cudainterp2.m, bilininterp/test_results_bilininterp_vs_cudainterp2_GPU_8800_GTX.png, bilininterp/test_results_bilininterp_vs_cudainterp2_GPU_9600M_GT.png, license.txt

Tags for This File
Everyone's Tags	bilinear, cuda, gpu, image processing, interp2, interpolation, mex
Tags I've Applied
Add New Tags	Please login to tag files.

Comments and Ratings (6)
21 Apr 2009	Yi Cao	The code works as described. On my GeForce 8400 GPU, it can achieve over 200 on relative speedup. The nvmex compiler also works smoothly on MATLAB R2009A. Excellent!
12 Jul 2009	Darius	Having trouble getting it running: "Can't locate File/Temp.pm in @INC (@INC contains: C:/Program Files/MATLAB/R2007a...)" How does one ensure valid "include" and "library" paths in "build_mex.m" ?
24 Jul 2009	Gerald Buchgraber	Dear Darius, you can find all build params described in nvmex.m For adding additional include or library paths just use (similar to gcc) the params: -I<pathname> (for include path), -L<directory> (for lib dir) and -l<name> (for lib file). Hopefully this helps and you get it running!
25 Sep 2009	Oliver Woodford	Is this supposed to compile on linux, or only on Windows? I can't get it to compile on linux.
28 Sep 2009	Gerald Buchgraber	Well, I haven't tried it yet, but I'm sure it's possible. The included build tools are dedicated to MS Windows. Please leave a notice if you get it running.
29 Sep 2009	Oliver Woodford	I wrote my own compile script for linux. See: http://www.mathworks.com/matlabcentral/newsreader/view_thread/261866

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Updates
20 Apr 2009	description changed
22 Apr 2009	added another picture showing the test results on a GeForce 8800 GTX. Much better results in comparision to my mobile GeForce ;)
19 May 2009	License changed to BSD
30 Jun 2009	I fixed a typo and added tags.

Tag Activity for this File
Tag	Applied By	Date/Time
bilinear	Gerald Buchgraber	16 Apr 2009 09:56:33
interpolation	Gerald Buchgraber	16 Apr 2009 09:56:33
cuda	Gerald Buchgraber	16 Apr 2009 09:56:33
image processing	Gerald Buchgraber	16 Apr 2009 09:56:33
mex	Gerald Buchgraber	16 Apr 2009 09:56:33
interp2	Gerald Buchgraber	30 Jun 2009 11:13:44
gpu	Gerald Buchgraber	30 Jun 2009 11:13:45

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