[passed difference speedup] = ConvolutionKernelTest(win, nrinchannels, nroutchannels, kernel1, kernel2, imgsize, shadertype, debug)

Test Psychtoolbox imaging pipeline’s 2D convolution shaders for
correctness and accuracy, perform speed benchmark, return fastest setup,
when using a specific (pair) of kernel(s) and parameters.

This routine builds and tests a set of convolution shaders from the given
convolution kernel (or pair of kernels for separable dual-pass
convolution). Each shader is compared against the results of
Matlabs/Octaves conv2 function, applied to a random noise luminance image
matrix. The shader is tagged as working correctly if the conv2 result and
PTB’s result do not disagree by more than 1 unit at any location in the
convolved output images. Accuracy (maximum difference) is reported. All
correctly working shaders are then benchmarked for speed during a test
period of 10 seconds and the speedup of the GPU vs. Matlab (CPU) is
determined and reported. At the end, the best configuration (wrt.
correctness, accuracy and speed) is reported/recommended for use with the
given kernel.

The routine takes at least 10 seconds per tested shader, so a full test
run will take at least 4*10 = 40 seconds, probably a bit more for setup
and shutdown. Status messages will tell you about progress of the
operation. You shouldn’t use your machine and don’t run any other
applications during benchmarking, otherwise the measured speedup numbers
may be wrong due to GPU or CPU overload.

Optional parameters and their defaults:

‘win’ Window handle of the onscreen window to test on. If none provided,
will open a suitable one by itself on screen 0.

‘nrinchannels’ number of image color channels in test image: Default is 1
for pure luminance convolution. This script always only tests the first
channel (red/luminance) for correctness/accuracy, even on multi-channel
images, but choice of channels will affect overall correctness and speed.

‘nroutchannels’ number of image output channels from convolution: By
default 1 == convolve, replicate result to RGB channels, pass alpha
through. 3 == Convolve RGB separately, pass through alpha. 4 == Convolve
RGBA separately.

‘kernel1’ == 2D kernel or first 1D kernel in separable mode.
‘kernel2’ == 1D kernel for 2nd pass in separable convolution test.

‘imgsize’ == Either size of the random noise test image (default =
512x512), or a Matlab image matrix to test on.

‘shadertype’ == Vector of mode ids: Tests all modes in the vector. By
default all shadertypes are tested ie shadertype = [0 1 2 3]. PTB
provides different implementations of convolution (0,1,2,3) which may
have different accuracy and performance for a given hardware and kernel.
The shaders provided in this vector will be tested against each other.

‘debug’Defaults to zero (no output): Amount of debug output to write to
Matlab window.


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