SumNeuron commented on issue #7900: Request: finish python gpu enabled guide for install URL: https://github.com/apache/incubator-mxnet/issues/7900#issuecomment-330127202 #------------------------------------------------------------------------------- # Template configuration for compiling mxnet # # If you want to change the configuration, please use the following # steps. Assume you are on the root directory of mxnet. First copy the this # file so that any local changes will be ignored by git # # $ cp make/config.mk . # # Next modify the according entries, and then compile by # # $ make # # or build in parallel with 8 threads # # $ make -j8 #------------------------------------------------------------------------------- #--------------------- # choice of compiler #-------------------- export CC = gcc export CXX = g++ export NVCC = nvcc # whether compile with options for MXNet developer DEV = 0 # whether compile with debug DEBUG = 0 # the additional link flags you want to add ADD_LDFLAGS = # the additional compile flags you want to add ADD_CFLAGS = #--------------------------------------------- # matrix computation libraries for CPU/GPU #--------------------------------------------- # whether use CUDA during compile USE_CUDA = 0 # add the path to CUDA library to link and compile flag # if you have already add them to environment variable, leave it as NONE # USE_CUDA_PATH = /usr/local/cuda USE_CUDA_PATH = NONE # whether use CUDNN R3 library USE_CUDNN = 0 # whether use cuda runtime compiling for writing kernels in native language (i.e. Python) USE_NVRTC = 0 # whether use opencv during compilation # you can disable it, however, you will not able to use # imbin iterator USE_OPENCV = 1 # use openmp for parallelization USE_OPENMP = 0 # choose the version of blas you want to use # can be: mkl, blas, atlas, openblas USE_BLAS = apple # whether use lapack during compilation # only effective when compiled with blas versions openblas/apple/atlas/mkl USE_LAPACK = 1 # add path to intel library, you may need it for MKL, if you did not add the path # to environment variable USE_INTEL_PATH = NONE #---------------------------- # distributed computing #---------------------------- # whether or not to enable multi-machine supporting USE_DIST_KVSTORE = 0 # whether or not allow to read and write HDFS directly. If yes, then hadoop is # required USE_HDFS = 0 # path to libjvm.so. required if USE_HDFS=1 LIBJVM=$(JAVA_HOME)/jre/lib/amd64/server # whether or not allow to read and write AWS S3 directly. If yes, then # libcurl4-openssl-dev is required, it can be installed on Ubuntu by # sudo apt-get install -y libcurl4-openssl-dev USE_S3 = 0 #---------------------------- # additional operators #---------------------------- # path to folders containing projects specific operators that you don't want to put in src/operators EXTRA_OPERATORS = #---------------------------- # other features #---------------------------- # Create C++ interface package USE_CPP_PACKAGE = 0 #---------------------------- # plugins #---------------------------- # whether to use torch integration. This requires installing torch. # TORCH_PATH = $(HOME)/torch # MXNET_PLUGINS += plugin/torch/torch.mk USE_BLAS = openblas ADD_CFLAGS += -I/usr/local/opt/openblas/include ADD_LDFLAGS += -L/usr/local/opt/openblas/lib ADD_LDFLAGS += -L/usr/local/lib/graphviz/ USE_CUDA = 1 USE_CUDA_PATH = /usr/local/cuda USE_CUDNN = 1 ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
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