Added cudnn_frontend api in caffe to support CUDA11+cuDNN8#2184
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cheneeheng wants to merge 1 commit intoCMU-Perceptual-Computing-Lab:masterfrom
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Added cudnn_frontend api in caffe to support CUDA11+cuDNN8#2184cheneeheng wants to merge 1 commit intoCMU-Perceptual-Computing-Lab:masterfrom
cheneeheng wants to merge 1 commit intoCMU-Perceptual-Computing-Lab:masterfrom
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- added cudnn-frontend submodule - updated cmake - changed caffe submodule repo target
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I tested this setup with CUDA11.7 + cuDNN8.5 on a GTX1660TI. It runs openpose for human pose extraction normally without the huge GPU memory usage issue. The GPU memory usage is the same as the CUDA10.2+cuDNN7 setup, while the inference speed is about ~1fps faster.
Hope this helps someone who needs to use CUDA11 very badly.
Changelog:
cudnn_frontend.-- added
DUSE_CUDNN_FRONTENDoption. Uses the frontend api instead of the current algorithm wrappercudnnGetConvolutionForwardAlgorithm_v7for cuDNN8.-- added
cudnn_v8_utils.hpp+cudnn_v8_utils.cppfiles for cudnn_frontend api. It currently only supports forwardpass.-- fixed warnings.
-- reduced GPU memory usage by setting CUDNN_STREAMS_PER_GROUP=1
-- added compute capability check in tensor creation to enable tensor core usage in ampere cards.