The table below lists all the MATLAB Image Processing Toolbox (IPT) functions that we have implemented in OpenCL.
For each function, there is a link to a separate web page, which includes the source code, the usage, current data type support and the
implemented algorithm, the MATLAB command line example for that particular function.
* The execution time obtained through the original functions provided by MATLAB on CPU.
# GPU Total presents two numbers.
The first number is the total execution time obtained through running the GPU-accelerated functions, including pure kernel execution time,
CPU-GPU data transfer time, MEX-interface overhead.
The second number (x) indicates the speedup of GPU Total over MATLAB CPU.
$ GPU Kernel presents two numbers.
The first number is the pure kernel execution time.
The second number (x%) indicates the percentage of GPU Kernel over GPU Total.
Computing environment and experiment setup:
hardware and software: Windows XP 32-bit, MATLAB 2008a, Intel CPU Q6600 2.4GHz and ATI Radeon 5870.
Input Data: Performance results are obtained on 2K x 2K images of random values by default.
(radon is with 320 angles and a 512 X 512 image, bwdist is with a 1024 x 1024 image)
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