Open rtobar opened 6 years ago
ping
thanks for the detailed report; but this is beyond our (clFFT maintainers) normal scope of support, and clFFT is mostly in maintenance mode with only critical issues looked at. I hope someone in the community with experience in Beignet/Intel GPU could help you.
Hi @bragadeesh,
Thanks a lot for your reply, and for clarifying the actual state of the project. I think I will desist then on using clfft for the moment, until I have more time to investigate this issue on my side.
Hi,
I began using clfft (2.12.2, pre-built version shipped with Ubuntu 17.10) recently to perform 2D convolution of images. However, when testing on my currently available devices my code gives different results for the forward transform depending on the device I choose, and on whether I attach a pre-callback or not. In particular, clfft seems to be using the incorrect input data.
A few more details:
The operations I'm then doing are as follow:
input[offset]
makes the trick.I've generated the kernels resulting from the different combinations (intel v/s pocl, and no pre-callback v/s pre-callback), so I get 8 files (there is a Stockham2 and a Stockham3 file for each combination above). All Stockham3 kernels look identical, but the Stockham2 kernels differ a bit between the non-pre-callback and the pre-callback cases (but are identical for the two devices on each case):
clfft.kernel.Stockham3.cl-intel-cb.txt clfft.kernel.Stockham2.cl-intel-cb.txt clfft.kernel.Stockham3.cl-pocl-cb.txt clfft.kernel.Stockham2.cl-pocl-cb.txt clfft.kernel.Stockham3.cl-pocl-nocb.txt clfft.kernel.Stockham2.cl-pocl-nocb.txt clfft.kernel.Stockham3.cl-intel-nocb.txt clfft.kernel.Stockham2.cl-intel-nocb.txt
Please let me know if you need more information, or if I'm missing something terribly obvious.