Rank: 2108 based on 57 downloads (last 30 days) and 3 files submitted
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Jun Tan

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UT Southwestern Medical Center

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20 Aug 2014 Screenshot 3D image viewer and slicer A fast 3D image viewer and slicer that provides measurement, statistics, and visualization tools. Author: Jun Tan 3d image, viewer, slicer, image statistics, region measurement, line measurement 28 0
19 Aug 2014 Screenshot 3D trilinear interpolation using GPU 3D trilinear interpolation using GPU. 20 times faster. Author: Jun Tan 3d trilinear interpol..., interp3, interpolation, trilinear, cuda, gpu 21 2
  • 5.0
5.0 | 1 rating
10 Sep 2013 poly2mask using GPU poly2mask using GPU. Author: Jun Tan poly2mask, gpu, polygon to mask 8 0
Comments and Ratings by Jun Tan
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22 Feb 2013 3D trilinear interpolation using GPU 3D trilinear interpolation using GPU. 20 times faster. Author: Jun Tan

Hi, Raphael:

Thanks for your comments.

My program uses a persistent variable "k_interp3" (the kernel) in file "interp3_gpu.m". This variable is created the first time it is used, and remains in memory until you clear the variable manually or you close your Matlab.

The reason that I use the persistent variable is that the kernel only needs to be created once in order to save the time spent in creating it. Matlab is actually slow in creating it. So I don't want to create it every time I need to call interp3_gpu.m.

Moreover, if you clear the variable, my program can recreate k_interp3 again when it notices that the variable doesn't exist. I believe the minor memory cost is not a problem, so I leave it up to the users to clear it when needed.

My test shows that when I run command "clear all" and "gpuDevice", the "FreeMemory" value returns to its original value.

I hope I have answered your question.

Good luck,
Jun

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04 Aug 2014 3D trilinear interpolation using GPU 3D trilinear interpolation using GPU. 20 times faster. Author: Jun Tan Philip

22 Feb 2013 3D trilinear interpolation using GPU 3D trilinear interpolation using GPU. 20 times faster. Author: Jun Tan Jun Tan

Hi, Raphael:

Thanks for your comments.

My program uses a persistent variable "k_interp3" (the kernel) in file "interp3_gpu.m". This variable is created the first time it is used, and remains in memory until you clear the variable manually or you close your Matlab.

The reason that I use the persistent variable is that the kernel only needs to be created once in order to save the time spent in creating it. Matlab is actually slow in creating it. So I don't want to create it every time I need to call interp3_gpu.m.

Moreover, if you clear the variable, my program can recreate k_interp3 again when it notices that the variable doesn't exist. I believe the minor memory cost is not a problem, so I leave it up to the users to clear it when needed.

My test shows that when I run command "clear all" and "gpuDevice", the "FreeMemory" value returns to its original value.

I hope I have answered your question.

Good luck,
Jun

22 Feb 2013 3D trilinear interpolation using GPU 3D trilinear interpolation using GPU. 20 times faster. Author: Jun Tan Raphael

Hello!
In my opinion you have some trouble with memory usage in your code.
If I check the gpu-Memory with gpu.FreeMemory before and after your program running with bigger matrices there is some memory blocked.

Up to now i could not find out how to solve the problem. I suppose there is a problem with the use of feval.
If i use the feval function with an empty kernel i have the same problem...
Greeting, Raphael

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