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sanghoon / pva-faster-rcnn

Demo code for PVANet
https://arxiv.org/abs/1611.08588
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about cudnn #13

Closed duanLH closed 7 years ago

duanLH commented 7 years ago

you said "Do NOT uncomment USE_CUDNN := 1 (for running PVANET, cuDNN is slower than Caffe native implementation)", I want to know, the slower is include training and test? I train my net without cudnn, its so slow

sanghoon commented 7 years ago

I'm sorry we made a confusion here. It's totally okay to uncomment USE_CUDNN if it makes your training faster. It just means that commenting 'USE_CUDNN' worked faster in our computational environments.

I'll update README.

FYI, for our published results, training of a network took 7~14 days with Titan X or GTX1080.

happyharrycn commented 7 years ago

I think it is possible to also make testing faster with cuDNN, although I have not got a chance to test it on PVANET. The performance issue is that cuDNN had bad implementations for certain convolutions (e.g. 1x1 convolutions with stride=1, which is used a couple of times in PVANET). You can still compile Caffe with cuDNN and put engine: CAFFE under convolution_param in these layers.

jay2002 commented 7 years ago

@happyharrycn cool solution! I have tried it and it really does work