Caffe is a deep learning framework.
Cuda + cuDNN
On machines with GPUs and the NVIDIA driver installed, you can build Caffe with CUDA and cuDNN. Please note that there may be newer versions of CUDA and cuDNN available in the module tree than the listed ones below.
nvidia-smi -L to verify the NVIDIA driver is installed and can see your GPUs:
$ nvidia-smi -L GPU 0: GeForce GTX TITAN X (UUID: GPU-dd20c890-3d0f-942f-6e85-7b43c6bd03c5) GPU 1: GeForce GTX TITAN X (UUID: GPU-b1d93efa-3d89-bb58-d4cb-b517ead36b27)
Add the modules, clone the Caffe repository, configure the Makefile options, and build.
$ module add cuda/8.0.44 cudnn/v5.1 $ git clone https://github.com/BVLC/caffe.git Cloning into 'caffe'... remote: Counting objects: 37328, done. remote: Compressing objects: 100% (11/11), done. remote: Total 37328 (delta 11), reused 7 (delta 7), pack-reused 37310 Receiving objects: 100% (37328/37328), 47.48 MiB | 17.52 MiB/s, done. Resolving deltas: 100% (24927/24927), done. $ cd caffe/ $ cp Makefile.config.example Makefile.config # Set the following options in Makefile.config (uncomment). Make sure there are no trailing whitespace after these options. # USE_CUDNN := 1 # BLAS := open # CUDA_DIR := /opt/common/cuda/cuda-8.0.44/ $ make ... $ make test ...
If you need to use then please use Matlab 2015a and make sure you do the following commands in addition to what is above. Currently Matlab 2015a only supports GCC 4.7.x for compiling mex files.
module add matlab/2015a gcc/4.7.4 make matcaffe
To build Caffe with CPU-only capability, follow these instructions.
git clone https://github.com/BVLC/caffe.git cd caffe cp Makefile.config.example Makefile.config # set the following options in a Makefile.config # CPUONLY := 1 # BLAS := open make make test make runtest