This project will no longer be maintained by Intel. Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project. Intel no longer accepts patches to this project.
Nervana's fork of Alex Krizhevsky's cuda-convnet2 containing several extensions including:
- new python backend called cudanet for integration into Nervana's neon framework
- several new kernels and functions to support things like multiway costs, python interface to GPU memory, support for non-texture kernels, array and scalar max/min comparisons, local contrast normalization.
- one line pip or cmake based installation
- additional checking and fixes.
First ensure that you have met all required depdendency packges, as described on the cuda-convnet2 compilation page.
# Clone this repository.
git clone [email protected]:NervanaSystems/cuda-convnet2.git
cd cuda-convnet2
mkdir build
cd build
cmake ..
make install #for system-wide install, or else just make
The libraries will be added in the /usr/local/lib/ location. This path needs
to be in the LD_LIBRARY_PATH environment variable.
If there are issues with finding helper_cuda.h add it to the paths:
cmake -D CUDA_COMMON_INCLUDE_DIRS=[helper_cuda_path] -D CUDA_SDK_SEARCH_PATH=[helper_cuda_path] ..
or directly in the top-level CMakeLists.txt in find_path(CUDA_COMMON_INCLUDE_DIRS
helper_cuda.h ... )
If there are issues with linking OpenCV: Change the following: in make-data/pyext/CMakeLists.txt
set(OpenCV_LIBRARIES "-lopencv_core -lopencv_imgproc -lopencv_highgui -lopencv_ml -lopencv_video -lopencv_features2d -lopencv_calib3d -lopencv_objdetect -lopencv_contrib -lopencv_legacy -lopencv_flann -I/usr/include/opencv2 -L/usr/lib")
If there are issues opening libcconv2_cudanet.so make sure the permissions of
the libraries in /usr/local/lib/ are set correctly.