#.rst:
# FindCUDA
# --------
#
# .. note::
#
#   The FindCUDA module has been superseded by first-class support
#   for the CUDA language in CMake.  It is no longer necessary to
#   use this module or call ``find_package(CUDA)``.  This module
#   now exists only for compatibility with projects that have not
#   been ported.
#
#   Instead, list ``CUDA`` among the languages named in the top-level
#   call to the :command:`project` command, or call the
#   :command:`enable_language` command with ``CUDA``.
#   Then one can add CUDA (``.cu``) sources to programs directly
#   in calls to :command:`add_library` and :command:`add_executable`.
#
# Tools for building CUDA C files: libraries and build dependencies.
#
# This script locates the NVIDIA CUDA C tools.  It should work on Linux,
# Windows, and macOS and should be reasonably up to date with CUDA C
# releases.
#
# This script makes use of the standard :command:`find_package` arguments of
# ``<VERSION>``, ``REQUIRED`` and ``QUIET``.  ``CUDA_FOUND`` will report if an
# acceptable version of CUDA was found.
#
# The script will prompt the user to specify ``CUDA_TOOLKIT_ROOT_DIR`` if
# the prefix cannot be determined by the location of nvcc in the system
# path and ``REQUIRED`` is specified to :command:`find_package`.  To use
# a different installed version of the toolkit set the environment variable
# ``CUDA_BIN_PATH`` before running cmake (e.g.
# ``CUDA_BIN_PATH=/usr/local/cuda1.0`` instead of the default
# ``/usr/local/cuda``) or set ``CUDA_TOOLKIT_ROOT_DIR`` after configuring.  If
# you change the value of ``CUDA_TOOLKIT_ROOT_DIR``, various components that
# depend on the path will be relocated.
#
# It might be necessary to set ``CUDA_TOOLKIT_ROOT_DIR`` manually on certain
# platforms, or to use a CUDA runtime not installed in the default
# location.  In newer versions of the toolkit the CUDA library is
# included with the graphics driver -- be sure that the driver version
# matches what is needed by the CUDA runtime version.
#
# The following variables affect the behavior of the macros in the
# script (in alphebetical order).  Note that any of these flags can be
# changed multiple times in the same directory before calling
# ``CUDA_ADD_EXECUTABLE``, ``CUDA_ADD_LIBRARY``, ``CUDA_COMPILE``,
# ``CUDA_COMPILE_PTX``, ``CUDA_COMPILE_FATBIN``, ``CUDA_COMPILE_CUBIN``
# or ``CUDA_WRAP_SRCS``::
#
#   CUDA_64_BIT_DEVICE_CODE (Default matches host bit size)
#   -- Set to ON to compile for 64 bit device code, OFF for 32 bit device code.
#      Note that making this different from the host code when generating object
#      or C files from CUDA code just won't work, because size_t gets defined by
#      nvcc in the generated source.  If you compile to PTX and then load the
#      file yourself, you can mix bit sizes between device and host.
#
#   CUDA_ATTACH_VS_BUILD_RULE_TO_CUDA_FILE (Default ON)
#   -- Set to ON if you want the custom build rule to be attached to the source
#      file in Visual Studio.  Turn OFF if you add the same cuda file to multiple
#      targets.
#
#      This allows the user to build the target from the CUDA file; however, bad
#      things can happen if the CUDA source file is added to multiple targets.
#      When performing parallel builds it is possible for the custom build
#      command to be run more than once and in parallel causing cryptic build
#      errors.  VS runs the rules for every source file in the target, and a
#      source can have only one rule no matter how many projects it is added to.
#      When the rule is run from multiple targets race conditions can occur on
#      the generated file.  Eventually everything will get built, but if the user
#      is unaware of this behavior, there may be confusion.  It would be nice if
#      this script could detect the reuse of source files across multiple targets
#      and turn the option off for the user, but no good solution could be found.
#
#   CUDA_BUILD_CUBIN (Default OFF)
#   -- Set to ON to enable and extra compilation pass with the -cubin option in
#      Device mode. The output is parsed and register, shared memory usage is
#      printed during build.
#
#   CUDA_BUILD_EMULATION (Default OFF for device mode)
#   -- Set to ON for Emulation mode. -D_DEVICEEMU is defined for CUDA C files
#      when CUDA_BUILD_EMULATION is TRUE.
#
#   CUDA_LINK_LIBRARIES_KEYWORD (Default "")
#    -- The <PRIVATE|PUBLIC|INTERFACE> keyword to use for internal
#       target_link_libraries calls. The default is to use no keyword which
#       uses the old "plain" form of target_link_libraries. Note that is matters
#       because whatever is used inside the FindCUDA module must also be used
#       outside - the two forms of target_link_libraries cannot be mixed.
#
#   CUDA_GENERATED_OUTPUT_DIR (Default CMAKE_CURRENT_BINARY_DIR)
#   -- Set to the path you wish to have the generated files placed.  If it is
#      blank output files will be placed in CMAKE_CURRENT_BINARY_DIR.
#      Intermediate files will always be placed in
#      CMAKE_CURRENT_BINARY_DIR/CMakeFiles.
#
#   CUDA_HOST_COMPILATION_CPP (Default ON)
#   -- Set to OFF for C compilation of host code.
#
#   CUDA_HOST_COMPILER (Default CMAKE_C_COMPILER)
#   -- Set the host compiler to be used by nvcc.  Ignored if -ccbin or
#      --compiler-bindir is already present in the CUDA_NVCC_FLAGS or
#      CUDA_NVCC_FLAGS_<CONFIG> variables.  For Visual Studio targets,
#      the host compiler is constructed with one or more visual studio macros
#      such as $(VCInstallDir), that expands out to the path when
#      the command is run from within VS.
#      If the CUDAHOSTCXX environment variable is set it will
#      be used as the default.
#
#   CUDA_NVCC_FLAGS
#   CUDA_NVCC_FLAGS_<CONFIG>
#   -- Additional NVCC command line arguments.  NOTE: multiple arguments must be
#      semi-colon delimited (e.g. --compiler-options;-Wall)
#
#   CUDA_PROPAGATE_HOST_FLAGS (Default ON)
#   -- Set to ON to propagate CMAKE_{C,CXX}_FLAGS and their configuration
#      dependent counterparts (e.g. CMAKE_C_FLAGS_DEBUG) automatically to the
#      host compiler through nvcc's -Xcompiler flag.  This helps make the
#      generated host code match the rest of the system better.  Sometimes
#      certain flags give nvcc problems, and this will help you turn the flag
#      propagation off.  This does not affect the flags supplied directly to nvcc
#      via CUDA_NVCC_FLAGS or through the OPTION flags specified through
#      CUDA_ADD_LIBRARY, CUDA_ADD_EXECUTABLE, or CUDA_WRAP_SRCS.  Flags used for
#      shared library compilation are not affected by this flag.
#
#   CUDA_PROPAGATE_HOST_FLAGS_BLACKLIST (Default "")
#   -- A list containing the host flags that should not be propagated when
#      CUDA_PROPAGATE_HOST_FLAGS is ON.
#
#   CUDA_SEPARABLE_COMPILATION (Default OFF)
#   -- If set this will enable separable compilation for all CUDA runtime object
#      files.  If used outside of CUDA_ADD_EXECUTABLE and CUDA_ADD_LIBRARY
#      (e.g. calling CUDA_WRAP_SRCS directly),
#      CUDA_COMPUTE_SEPARABLE_COMPILATION_OBJECT_FILE_NAME and
#      CUDA_LINK_SEPARABLE_COMPILATION_OBJECTS should be called.
#
#   CUDA_SOURCE_PROPERTY_FORMAT
#   -- If this source file property is set, it can override the format specified
#      to CUDA_WRAP_SRCS (OBJ, PTX, CUBIN, or FATBIN).  If an input source file
#      is not a .cu file, setting this file will cause it to be treated as a .cu
#      file. See documentation for set_source_files_properties on how to set
#      this property.
#
#   CUDA_USE_STATIC_CUDA_RUNTIME (Default ON)
#   -- When enabled the static version of the CUDA runtime library will be used
#      in CUDA_LIBRARIES.  If the version of CUDA configured doesn't support
#      this option, then it will be silently disabled.
#
#   CUDA_VERBOSE_BUILD (Default OFF)
#   -- Set to ON to see all the commands used when building the CUDA file.  When
#      using a Makefile generator the value defaults to VERBOSE (run make
#      VERBOSE=1 to see output), although setting CUDA_VERBOSE_BUILD to ON will
#      always print the output.
#
# The script creates the following macros (in alphebetical order)::
#
#   CUDA_ADD_CUFFT_TO_TARGET( cuda_target )
#   -- Adds the cufft library to the target (can be any target).  Handles whether
#      you are in emulation mode or not.
#
#   CUDA_ADD_CUBLAS_TO_TARGET( cuda_target )
#   -- Adds the cublas library to the target (can be any target).  Handles
#      whether you are in emulation mode or not.
#
#   CUDA_ADD_EXECUTABLE( cuda_target file0 file1 ...
#                        [WIN32] [MACOSX_BUNDLE] [EXCLUDE_FROM_ALL] [OPTIONS ...] )
#   -- Creates an executable "cuda_target" which is made up of the files
#      specified.  All of the non CUDA C files are compiled using the standard
#      build rules specified by CMAKE and the cuda files are compiled to object
#      files using nvcc and the host compiler.  In addition CUDA_INCLUDE_DIRS is
#      added automatically to include_directories().  Some standard CMake target
#      calls can be used on the target after calling this macro
#      (e.g. set_target_properties and target_link_libraries), but setting
#      properties that adjust compilation flags will not affect code compiled by
#      nvcc.  Such flags should be modified before calling CUDA_ADD_EXECUTABLE,
#      CUDA_ADD_LIBRARY or CUDA_WRAP_SRCS.
#
#   CUDA_ADD_LIBRARY( cuda_target file0 file1 ...
#                     [STATIC | SHARED | MODULE] [EXCLUDE_FROM_ALL] [OPTIONS ...] )
#   -- Same as CUDA_ADD_EXECUTABLE except that a library is created.
#
#   CUDA_BUILD_CLEAN_TARGET()
#   -- Creates a convenience target that deletes all the dependency files
#      generated.  You should make clean after running this target to ensure the
#      dependency files get regenerated.
#
#   CUDA_COMPILE( generated_files file0 file1 ... [STATIC | SHARED | MODULE]
#                 [OPTIONS ...] )
#   -- Returns a list of generated files from the input source files to be used
#      with ADD_LIBRARY or ADD_EXECUTABLE.
#
#   CUDA_COMPILE_PTX( generated_files file0 file1 ... [OPTIONS ...] )
#   -- Returns a list of PTX files generated from the input source files.
#
#   CUDA_COMPILE_FATBIN( generated_files file0 file1 ... [OPTIONS ...] )
#   -- Returns a list of FATBIN files generated from the input source files.
#
#   CUDA_COMPILE_CUBIN( generated_files file0 file1 ... [OPTIONS ...] )
#   -- Returns a list of CUBIN files generated from the input source files.
#
#   CUDA_COMPUTE_SEPARABLE_COMPILATION_OBJECT_FILE_NAME( output_file_var
#                                                        cuda_target
#                                                        object_files )
#   -- Compute the name of the intermediate link file used for separable
#      compilation.  This file name is typically passed into
#      CUDA_LINK_SEPARABLE_COMPILATION_OBJECTS.  output_file_var is produced
#      based on cuda_target the list of objects files that need separable
#      compilation as specified by object_files.  If the object_files list is
#      empty, then output_file_var will be empty.  This function is called
#      automatically for CUDA_ADD_LIBRARY and CUDA_ADD_EXECUTABLE.  Note that
#      this is a function and not a macro.
#
#   CUDA_INCLUDE_DIRECTORIES( path0 path1 ... )
#   -- Sets the directories that should be passed to nvcc
#      (e.g. nvcc -Ipath0 -Ipath1 ... ). These paths usually contain other .cu
#      files.
#
#
#   CUDA_LINK_SEPARABLE_COMPILATION_OBJECTS( output_file_var cuda_target
#                                            nvcc_flags object_files)
#   -- Generates the link object required by separable compilation from the given
#      object files.  This is called automatically for CUDA_ADD_EXECUTABLE and
#      CUDA_ADD_LIBRARY, but can be called manually when using CUDA_WRAP_SRCS
#      directly.  When called from CUDA_ADD_LIBRARY or CUDA_ADD_EXECUTABLE the
#      nvcc_flags passed in are the same as the flags passed in via the OPTIONS
#      argument.  The only nvcc flag added automatically is the bitness flag as
#      specified by CUDA_64_BIT_DEVICE_CODE.  Note that this is a function
#      instead of a macro.
#
#   CUDA_SELECT_NVCC_ARCH_FLAGS(out_variable [target_CUDA_architectures])
#   -- Selects GPU arch flags for nvcc based on target_CUDA_architectures
#      target_CUDA_architectures : Auto | Common | All | LIST(ARCH_AND_PTX ...)
#       - "Auto" detects local machine GPU compute arch at runtime.
#       - "Common" and "All" cover common and entire subsets of architectures
#      ARCH_AND_PTX : NAME | NUM.NUM | NUM.NUM(NUM.NUM) | NUM.NUM+PTX
#      NAME: Kepler Maxwell Kepler+Tesla Maxwell+Tegra Pascal Volta Turing
#      NUM: Any number. Only those pairs are currently accepted by NVCC though:
#            3.5 3.7 5.0 5.2 5.3 6.0 6.1 6.2 7.0 7.2 7.5
#      Returns LIST of flags to be added to CUDA_NVCC_FLAGS in ${out_variable}
#      Additionally, sets ${out_variable}_readable to the resulting numeric list
#      Example:
#       CUDA_SELECT_NVCC_ARCH_FLAGS(ARCH_FLAGS 3.0 3.5+PTX 5.2(5.0) Maxwell)
#        LIST(APPEND CUDA_NVCC_FLAGS ${ARCH_FLAGS})
#
#      More info on CUDA architectures: https://en.wikipedia.org/wiki/CUDA
#      Note that this is a function instead of a macro.
#
#   CUDA_WRAP_SRCS ( cuda_target format generated_files file0 file1 ...
#                    [STATIC | SHARED | MODULE] [OPTIONS ...] )
#   -- This is where all the magic happens.  CUDA_ADD_EXECUTABLE,
#      CUDA_ADD_LIBRARY, CUDA_COMPILE, and CUDA_COMPILE_PTX all call this
#      function under the hood.
#
#      Given the list of files (file0 file1 ... fileN) this macro generates
#      custom commands that generate either PTX or linkable objects (use "PTX" or
#      "OBJ" for the format argument to switch).  Files that don't end with .cu
#      or have the HEADER_FILE_ONLY property are ignored.
#
#      The arguments passed in after OPTIONS are extra command line options to
#      give to nvcc.  You can also specify per configuration options by
#      specifying the name of the configuration followed by the options.  General
#      options must precede configuration specific options.  Not all
#      configurations need to be specified, only the ones provided will be used.
#
#         OPTIONS -DFLAG=2 "-DFLAG_OTHER=space in flag"
#         DEBUG -g
#         RELEASE --use_fast_math
#         RELWITHDEBINFO --use_fast_math;-g
#         MINSIZEREL --use_fast_math
#
#      For certain configurations (namely VS generating object files with
#      CUDA_ATTACH_VS_BUILD_RULE_TO_CUDA_FILE set to ON), no generated file will
#      be produced for the given cuda file.  This is because when you add the
#      cuda file to Visual Studio it knows that this file produces an object file
#      and will link in the resulting object file automatically.
#
#      This script will also generate a separate cmake script that is used at
#      build time to invoke nvcc.  This is for several reasons.
#
#        1. nvcc can return negative numbers as return values which confuses
#        Visual Studio into thinking that the command succeeded.  The script now
#        checks the error codes and produces errors when there was a problem.
#
#        2. nvcc has been known to not delete incomplete results when it
#        encounters problems.  This confuses build systems into thinking the
#        target was generated when in fact an unusable file exists.  The script
#        now deletes the output files if there was an error.
#
#        3. By putting all the options that affect the build into a file and then
#        make the build rule dependent on the file, the output files will be
#        regenerated when the options change.
#
#      This script also looks at optional arguments STATIC, SHARED, or MODULE to
#      determine when to target the object compilation for a shared library.
#      BUILD_SHARED_LIBS is ignored in CUDA_WRAP_SRCS, but it is respected in
#      CUDA_ADD_LIBRARY.  On some systems special flags are added for building
#      objects intended for shared libraries.  A preprocessor macro,
#      <target_name>_EXPORTS is defined when a shared library compilation is
#      detected.
#
#      Flags passed into add_definitions with -D or /D are passed along to nvcc.
#
#
#
# The script defines the following variables::
#
#   CUDA_VERSION_MAJOR    -- The major version of cuda as reported by nvcc.
#   CUDA_VERSION_MINOR    -- The minor version.
#   CUDA_VERSION
#   CUDA_VERSION_STRING   -- CUDA_VERSION_MAJOR.CUDA_VERSION_MINOR
#   CUDA_HAS_FP16         -- Whether a short float (float16,fp16) is supported.
#
#   CUDA_TOOLKIT_ROOT_DIR -- Path to the CUDA Toolkit (defined if not set).
#   CUDA_SDK_ROOT_DIR     -- Path to the CUDA SDK.  Use this to find files in the
#                            SDK.  This script will not directly support finding
#                            specific libraries or headers, as that isn't
#                            supported by NVIDIA.  If you want to change
#                            libraries when the path changes see the
#                            FindCUDA.cmake script for an example of how to clear
#                            these variables.  There are also examples of how to
#                            use the CUDA_SDK_ROOT_DIR to locate headers or
#                            libraries, if you so choose (at your own risk).
#   CUDA_INCLUDE_DIRS     -- Include directory for cuda headers.  Added automatically
#                            for CUDA_ADD_EXECUTABLE and CUDA_ADD_LIBRARY.
#   CUDA_LIBRARIES        -- Cuda RT library.
#   CUDA_CUFFT_LIBRARIES  -- Device or emulation library for the Cuda FFT
#                            implementation (alternative to:
#                            CUDA_ADD_CUFFT_TO_TARGET macro)
#   CUDA_CUBLAS_LIBRARIES -- Device or emulation library for the Cuda BLAS
#                            implementation (alternative to:
#                            CUDA_ADD_CUBLAS_TO_TARGET macro).
#   CUDA_cudart_static_LIBRARY -- Statically linkable cuda runtime library.
#                                 Only available for CUDA version 5.5+
#   CUDA_cudadevrt_LIBRARY -- Device runtime library.
#                             Required for separable compilation.
#   CUDA_cupti_LIBRARY    -- CUDA Profiling Tools Interface library.
#                            Only available for CUDA version 4.0+.
#   CUDA_curand_LIBRARY   -- CUDA Random Number Generation library.
#                            Only available for CUDA version 3.2+.
#   CUDA_cusolver_LIBRARY -- CUDA Direct Solver library.
#                            Only available for CUDA version 7.0+.
#   CUDA_cusparse_LIBRARY -- CUDA Sparse Matrix library.
#                            Only available for CUDA version 3.2+.
#   CUDA_npp_LIBRARY      -- NVIDIA Performance Primitives lib.