From bdba27251490b971e60d79261e14225cc7bfedcf Mon Sep 17 00:00:00 2001 From: Jegathesan Shanmugam Date: Thu, 26 Mar 2020 22:47:37 +0530 Subject: Github #111 Added Dockerfile to build ArmNN under an x86_64 system to target an Arm64 system. Signed-off-by: Jegathesan Shanmugam Change-Id: I244bab37cc5fe7b38a22d4b530d42e593f223d79 --- docker/x86_64/Makefile.config | 125 ++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 125 insertions(+) create mode 100644 docker/x86_64/Makefile.config (limited to 'docker/x86_64/Makefile.config') diff --git a/docker/x86_64/Makefile.config b/docker/x86_64/Makefile.config new file mode 100644 index 0000000000..7f9b196a30 --- /dev/null +++ b/docker/x86_64/Makefile.config @@ -0,0 +1,125 @@ +## Refer to http://caffe.berkeleyvision.org/installation.html +# Contributions simplifying and improving our build system are welcome! + +# cuDNN acceleration switch (uncomment to build with cuDNN). +# USE_CUDNN := 1 + +# CPU-only switch (uncomment to build without GPU support). +CPU_ONLY := 1 + +# uncomment to disable IO dependencies and corresponding data layers +# USE_OPENCV := 0 +# USE_LEVELDB := 0 +# USE_LMDB := 0 +# This code is taken from https://github.com/sh1r0/caffe-android-lib +# USE_HDF5 := 0 + +# uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary) +# You should not set this flag if you will be reading LMDBs with any +# possibility of simultaneous read and write +# ALLOW_LMDB_NOLOCK := 1 + +# Uncomment if you're using OpenCV 3 +# OPENCV_VERSION := 3 + +# To customize your choice of compiler, uncomment and set the following. +# N.B. the default for Linux is g++ and the default for OSX is clang++ +# CUSTOM_CXX := g++ + +# CUDA directory contains bin/ and lib/ directories that we need. +CUDA_DIR := /usr/local/cuda +# On Ubuntu 14.04, if cuda tools are installed via +# "sudo apt-get install nvidia-cuda-toolkit" then use this instead: +# CUDA_DIR := /usr + +# CUDA architecture setting: going with all of them. +# For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility. +# For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility. +# For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility. +CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \ + -gencode arch=compute_20,code=sm_21 \ + -gencode arch=compute_30,code=sm_30 \ + -gencode arch=compute_35,code=sm_35 \ + -gencode arch=compute_50,code=sm_50 \ + -gencode arch=compute_52,code=sm_52 \ + -gencode arch=compute_60,code=sm_60 \ + -gencode arch=compute_61,code=sm_61 \ + -gencode arch=compute_61,code=compute_61 + +# BLAS choice: +# atlas for ATLAS (default) +# mkl for MKL +# open for OpenBlas +BLAS := atlas +# Custom (MKL/ATLAS/OpenBLAS) include and lib directories. +# Leave commented to accept the defaults for your choice of BLAS +# (which should work)! +# BLAS_INCLUDE := /path/to/your/blas +# BLAS_LIB := /path/to/your/blas + +# Homebrew puts openblas in a directory that is not on the standard search path +# BLAS_INCLUDE := $(shell brew --prefix openblas)/include +# BLAS_LIB := $(shell brew --prefix openblas)/lib + +# This is required only if you will compile the matlab interface. +# MATLAB directory should contain the mex binary in /bin. +# MATLAB_DIR := /usr/local +# MATLAB_DIR := /Applications/MATLAB_R2012b.app + +# NOTE: this is required only if you will compile the python interface. +# We need to be able to find Python.h and numpy/arrayobject.h. +PYTHON_INCLUDE := /usr/include/python2.7 \ + /usr/lib/python2.7/dist-packages/numpy/core/include +# Anaconda Python distribution is quite popular. Include path: +# Verify anaconda location, sometimes it's in root. +# ANACONDA_HOME := $(HOME)/anaconda +# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \ + # $(ANACONDA_HOME)/include/python2.7 \ + # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include + +# Uncomment to use Python 3 (default is Python 2) +# PYTHON_LIBRARIES := boost_python3 python3.5m +# PYTHON_INCLUDE := /usr/include/python3.5m \ +# /usr/lib/python3.5/dist-packages/numpy/core/include + +# We need to be able to find libpythonX.X.so or .dylib. +PYTHON_LIB := /usr/lib +# PYTHON_LIB := $(ANACONDA_HOME)/lib + +# Homebrew installs numpy in a non standard path (keg only) +# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include +# PYTHON_LIB += $(shell brew --prefix numpy)/lib + +# Uncomment to support layers written in Python (will link against Python libs) +# WITH_PYTHON_LAYER := 1 + +# Whatever else you find you need goes here. +INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/ \ + /root/armnn-devenv/google/x86_64_pb_install/include/ +LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial/ \ + /root/armnn-devenv/google/x86_64_pb_install/lib/ + +# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies +# INCLUDE_DIRS += $(shell brew --prefix)/include +# LIBRARY_DIRS += $(shell brew --prefix)/lib + +# NCCL acceleration switch (uncomment to build with NCCL) +# https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0) +# USE_NCCL := 1 + +# Uncomment to use `pkg-config` to specify OpenCV library paths. +# (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.) +# USE_PKG_CONFIG := 1 + +# N.B. both build and distribute dirs are cleared on `make clean` +BUILD_DIR := build +DISTRIBUTE_DIR := distribute + +# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171 +# DEBUG := 1 + +# The ID of the GPU that 'make runtest' will use to run unit tests. +TEST_GPUID := 0 + +# enable pretty build (comment to see full commands) +Q ?= @ -- cgit v1.2.1