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Hello,
I used Intel MKL VSL functions to do image convolution. We found normally the VSL_CONV_MODE_FFT mode runs faster for large image and large kernel combinations. However, I tried an 8k by 8k 4byte float image and a 5 by 5 float kernel with VslsConv2d in VSL_CONV_MODE_FFT mode. The process took almost all my computer remaining memory about 3G and a few minutes to finish. If we try a 7k by 7k float image and a 5 by 5 kernel. It only takes a few seconds to finish. Is it a bug in MKL? Thanks.
I used Intel MKL VSL functions to do image convolution. We found normally the VSL_CONV_MODE_FFT mode runs faster for large image and large kernel combinations. However, I tried an 8k by 8k 4byte float image and a 5 by 5 float kernel with VslsConv2d in VSL_CONV_MODE_FFT mode. The process took almost all my computer remaining memory about 3G and a few minutes to finish. If we try a 7k by 7k float image and a 5 by 5 kernel. It only takes a few seconds to finish. Is it a bug in MKL? Thanks.
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Hello,
that's happens because of swapping problem and the RAM size is not enough on your system.
for example, I checked how it works on the my side ( RAM ==32 Gb) and here are the results I had:
size == 5000, execTime == 0.610678 sec
size == 7000, execTime == 0.730076 sec
size == 8000, execTime == 0.761053 sec
checked with the latest MKL v.10.3 Update 11 and MKL 11.0 ( which we are going to release soon)
OS - Lin64, lp64. threading
--Gennady
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