incubator-mxnet-1.9.0/config/linux_arm.cmake

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# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
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# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

#-------------------------------------------------------------------------------
#  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 this file so that
#  any local changes will be ignored by git
#
#  $ cp config/linux_arm.cmake config.cmake
#
#  Next modify the according entries, and then compile by
#
#  $ mkdir build; cd build
#  $ cmake ..
#  $ cmake --build .
#
# Specify `cmake --build . --parallel N` to set the number of parallel compilation jobs.
# Default is derived from CPUs available.
#
#-------------------------------------------------------------------------------

#---------------------------------------------
# Arm flags
#---------------------------------------------
# Set the correct C and CXX flags according to your Arm processor's architecture
# e.g. "armv8-a"
set(CFLAGS "-march=armv8-a" CACHE STRING "CFLAGS")
set(CXXFLAGS "-march=armv8-a" CACHE STRING "CXXFLAGS")

#---------------------------------------------
# GPU support
#---------------------------------------------
set(USE_CUDA OFF CACHE BOOL "Build with CUDA support")
set(USE_CUDNN OFF CACHE BOOL "Build with cudnn support, if found")

# Target NVIDIA GPU achitecture.
# Valid options are "Auto" for autodetection, "All" for all available
# architectures or a list of architectures by compute capability number, such as
# "7.0" or "7.0;7.5" as well as name, such as "Volta" or "Volta;Turing".
# The value specified here is passed to cmake's CUDA_SELECT_NVCC_ARCH_FLAGS to
# obtain the compilation flags for nvcc.
#
# When compiling on a machine without GPU, autodetection will fail and you
# should instead specify the target architecture manually to avoid excessive
# compilation times.
set(MXNET_CUDA_ARCH "Auto" CACHE STRING "Target NVIDIA GPU achitecture")

#---------------------------------------------
# Common libraries
#---------------------------------------------
set(USE_BLAS "open" CACHE STRING "BLAS Vendor")

set(USE_OPENCV ON CACHE BOOL "Build with OpenCV support")
set(OPENCV_ROOT "" CACHE BOOL "OpenCV install path. Supports autodetection.")

set(USE_OPENMP ON CACHE BOOL "Build with Openmp support")

set(USE_MKL_IF_AVAILABLE ON CACHE BOOL "Use Intel MKL if found")
set(USE_MKLDNN ON CACHE BOOL "Build with MKL-DNN support")

set(USE_LAPACK ON CACHE BOOL "Build with lapack support")

set(USE_TVM_OP OFF CACHE BOOL "Enable use of TVM operator build system.")

# Integrate MKLDNN with Arm Performance Libraries
# Note that APL needs to be added to LD_LIBRARY_PATH
set(MKLDNN_USE_APL OFF CACHE BOOL "Integrate MKLDNN with Arm Performance Libraries")

# Integrate MKLDNN with Arm Compute Library
set(ENV{ACL_ROOT_DIR} "")
set(MKLDNN_USE_ACL OFF CACHE BOOL "Integrate MKLDNN with Arm Compute Library")

#---------------------
# Compilers
#--------------------
set(CMAKE_GENERATOR "Ninja" CACHE STRING "Build Tool Generator used by CMake")

# Compilers are usually autodetected. Uncomment and modify the next 3 lines to
# choose manually:

# set(CMAKE_C_COMPILER "" CACHE BOOL "C compiler")
# set(CMAKE_CXX_COMPILER "" CACHE BOOL "C++ compiler")
# set(CMAKE_CUDA_COMPILER "" CACHE BOOL "Cuda compiler (nvcc)")

# Uncomment the following line to compile with debug information
# set(CMAKE_BUILD_TYPE Debug CACHE STRING "CMake build type")

#---------------------------------------------
# CPU instruction sets: The support is autodetected if turned ON
#---------------------------------------------
set(USE_SSE OFF CACHE BOOL "Build with x86 SSE instruction support")
set(USE_F16C OFF CACHE BOOL "Build with x86 F16C instruction support")


#----------------------------
# distributed computing
#----------------------------
set(USE_DIST_KVSTORE OFF CACHE BOOL "Build with DIST_KVSTORE support")


#----------------------------
# performance settings
#----------------------------
set(USE_OPERATOR_TUNING ON CACHE BOOL  "Enable auto-tuning of operators")
set(USE_GPERFTOOLS OFF CACHE BOOL "Build with GPerfTools support")
set(USE_JEMALLOC OFF CACHE BOOL "Build with Jemalloc support")


#----------------------------
# additional operators
#----------------------------
# path to folders containing projects specific operators that you don't want to
# put in src/operators
SET(EXTRA_OPERATORS "" CACHE PATH "EXTRA OPERATORS PATH")


#----------------------------
# other features
#----------------------------
# Create C++ interface package
set(USE_CPP_PACKAGE OFF CACHE BOOL "Build C++ Package")

# Use int64_t type to represent the total number of elements in a tensor
# This will cause performance degradation reported in issue #14496
# Set to 1 for large tensor with tensor size greater than INT32_MAX i.e. 2147483647
# Note: the size of each dimension is still bounded by INT32_MAX
set(USE_INT64_TENSOR_SIZE OFF CACHE BOOL "Use int64_t to represent the total number of elements in a tensor")

# Other GPU features
set(USE_NCCL "Use NVidia NCCL with CUDA" OFF)
set(NCCL_ROOT "" CACHE BOOL "NCCL install path. Supports autodetection.")
set(ENABLE_CUDA_RTC OFF CACHE BOOL "Build with CUDA runtime compilation support")
set(USE_NVTX OFF CACHE BOOL "Build with NVTX support")