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Switch NCCL to build from open source (version 2.3.5-5) by default.

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Note to users manually patching ptxas from a later toolkit version:
Building NCCL requires the same version of ptxas and nvlink.

PiperOrigin-RevId: 215911973
This commit is contained in:
A. Unique TensorFlower 2018-10-05 08:46:54 -07:00 committed by TensorFlower Gardener
parent cea6b49591
commit 53faa313b7
8 changed files with 1565 additions and 1289 deletions
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17
configure.py
View File

@ -35,7 +35,6 @@ except ImportError:
_DEFAULT_CUDA_VERSION = '9.0'
_DEFAULT_CUDNN_VERSION = '7'
_DEFAULT_NCCL_VERSION = '2.2'
_DEFAULT_CUDA_COMPUTE_CAPABILITIES = '3.5,7.0'
_DEFAULT_CUDA_PATH = '/usr/local/cuda'
_DEFAULT_CUDA_PATH_LINUX = '/opt/cuda'
@ -1109,18 +1108,17 @@ def set_tf_nccl_install_path(environ_cp):
raise ValueError('Currently NCCL is only supported on Linux platforms.')
ask_nccl_version = (
'Please specify the NCCL version you want to use. If NCCL %s is not '
'installed, then you can use version 1.3 that can be fetched '
'automatically but it may have worse performance with multiple GPUs. '
'[Default is %s]: ') % (_DEFAULT_NCCL_VERSION, _DEFAULT_NCCL_VERSION)
'Please specify the locally installed NCCL version you want to use. '
'[Default is to use https://github.com/nvidia/nccl]: ')
for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS):
tf_nccl_version = get_from_env_or_user_or_default(
environ_cp, 'TF_NCCL_VERSION', ask_nccl_version, _DEFAULT_NCCL_VERSION)
tf_nccl_version = reformat_version_sequence(str(tf_nccl_version), 1)
environ_cp, 'TF_NCCL_VERSION', ask_nccl_version, '')
if tf_nccl_version == '1':
break # No need to get install path, NCCL 1 is a GitHub repo.
if not tf_nccl_version:
break # No need to get install path, building the open source code.
tf_nccl_version = reformat_version_sequence(str(tf_nccl_version), 1)
# Look with ldconfig first if we can find the library in paths
# like /usr/lib/x86_64-linux-gnu and the header file in the corresponding
@ -1232,7 +1230,6 @@ def set_tf_nccl_install_path(environ_cp):
environ_cp['TF_NCCL_VERSION'] = tf_nccl_version
write_action_env_to_bazelrc('TF_NCCL_VERSION', tf_nccl_version)
def get_native_cuda_compute_capabilities(environ_cp):
"""Get native cuda compute capabilities.

10
tensorflow/workspace.bzl
View File

@ -585,12 +585,12 @@ def tf_workspace(path_prefix = "", tf_repo_name = ""):
tf_http_archive(
name = "nccl_archive",
build_file = clean_dep("//third_party:nccl/nccl_archive.BUILD"),
sha256 = "2ca86fb6179ecbff789cc67c836139c1bbc0324ed8c04643405a30bf26325176",
strip_prefix = "nccl-03d856977ecbaac87e598c0c4bafca96761b9ac7",
build_file = clean_dep("//third_party:nccl/archive.BUILD"),
sha256 = "19132b5127fa8e02d95a09795866923f04064c8f1e0770b2b42ab551408882a4",
strip_prefix = "nccl-f93fe9bfd94884cec2ba711897222e0df5569a53",
urls = [
"https://mirror.bazel.build/github.com/nvidia/nccl/archive/03d856977ecbaac87e598c0c4bafca96761b9ac7.tar.gz",
"https://github.com/nvidia/nccl/archive/03d856977ecbaac87e598c0c4bafca96761b9ac7.tar.gz",
"https://mirror.bazel.build/github.com/nvidia/nccl/archive/f93fe9bfd94884cec2ba711897222e0df5569a53.tar.gz",
"https://github.com/nvidia/nccl/archive/f93fe9bfd94884cec2ba711897222e0df5569a53.tar.gz",
],
)

441
third_party/gpus/cuda_configure.bzl vendored
View File

@ -134,24 +134,28 @@ def _get_python_bin(repository_ctx):
python_bin_path = repository_ctx.which(python_bin_name)
if python_bin_path != None:
return str(python_bin_path)
auto_configure_fail("Cannot find python in PATH, please make sure " +
auto_configure_fail(
"Cannot find python in PATH, please make sure " +
"python is installed and add its directory in PATH, or --define " +
"%s='/something/else'.\nPATH=%s" % (
_PYTHON_BIN_PATH,
repository_ctx.os.environ.get("PATH", ""),
))
def _get_nvcc_tmp_dir_for_windows(repository_ctx):
"""Return the tmp directory for nvcc to generate intermediate source files."""
escaped_tmp_dir = escape_string(
get_env_var(repository_ctx, "TMP", "C:\\Windows\\Temp").replace("\\", "\\\\"),
)
get_env_var(repository_ctx, "TMP", "C:\\Windows\\Temp").replace(
"\\", "\\\\"),)
return escaped_tmp_dir + "\\\\nvcc_inter_files_tmp_dir"
def _get_msvc_compiler(repository_ctx):
vc_path = find_vc_path(repository_ctx)
return find_msvc_tool(repository_ctx, vc_path, "cl.exe").replace("\\", "/")
def _get_win_cuda_defines(repository_ctx):
"""Return CROSSTOOL defines for Windows"""
@ -172,8 +176,10 @@ def _get_win_cuda_defines(repository_ctx):
vc_path = find_vc_path(repository_ctx)
if not vc_path:
auto_configure_fail("Visual C++ build tools not found on your machine." +
"Please check your installation following https://docs.bazel.build/versions/master/windows.html#using")
auto_configure_fail(
"Visual C++ build tools not found on your machine." +
"Please check your installation following https://docs.bazel.build/versions/master/windows.html#using"
)
return {}
env = setup_vc_env_vars(repository_ctx, vc_path)
@ -181,31 +187,47 @@ def _get_win_cuda_defines(repository_ctx):
escaped_include_paths = escape_string(env["INCLUDE"])
escaped_lib_paths = escape_string(env["LIB"])
escaped_tmp_dir = escape_string(
get_env_var(repository_ctx, "TMP", "C:\\Windows\\Temp").replace("\\", "\\\\"),
)
get_env_var(repository_ctx, "TMP", "C:\\Windows\\Temp").replace(
"\\", "\\\\"),)
msvc_cl_path = "windows/msvc_wrapper_for_nvcc.bat"
msvc_ml_path = find_msvc_tool(repository_ctx, vc_path, "ml64.exe").replace("\\", "/")
msvc_link_path = find_msvc_tool(repository_ctx, vc_path, "link.exe").replace("\\", "/")
msvc_lib_path = find_msvc_tool(repository_ctx, vc_path, "lib.exe").replace("\\", "/")
msvc_ml_path = find_msvc_tool(repository_ctx, vc_path, "ml64.exe").replace(
"\\", "/")
msvc_link_path = find_msvc_tool(repository_ctx, vc_path, "link.exe").replace(
"\\", "/")
msvc_lib_path = find_msvc_tool(repository_ctx, vc_path, "lib.exe").replace(
"\\", "/")
# nvcc will generate some temporary source files under %{nvcc_tmp_dir}
# The generated files are guranteed to have unique name, so they can share the same tmp directory
escaped_cxx_include_directories = ["cxx_builtin_include_directory: \"%s\"" % _get_nvcc_tmp_dir_for_windows(repository_ctx)]
escaped_cxx_include_directories = [
"cxx_builtin_include_directory: \"%s\"" %
_get_nvcc_tmp_dir_for_windows(repository_ctx)
]
for path in escaped_include_paths.split(";"):
if path:
escaped_cxx_include_directories.append("cxx_builtin_include_directory: \"%s\"" % path)
escaped_cxx_include_directories.append(
"cxx_builtin_include_directory: \"%s\"" % path)
return {
"%{msvc_env_tmp}": escaped_tmp_dir,
"%{msvc_env_path}": escaped_paths,
"%{msvc_env_include}": escaped_include_paths,
"%{msvc_env_lib}": escaped_lib_paths,
"%{msvc_cl_path}": msvc_cl_path,
"%{msvc_ml_path}": msvc_ml_path,
"%{msvc_link_path}": msvc_link_path,
"%{msvc_lib_path}": msvc_lib_path,
"%{cxx_builtin_include_directory}": "\n".join(escaped_cxx_include_directories),
"%{msvc_env_tmp}":
escaped_tmp_dir,
"%{msvc_env_path}":
escaped_paths,
"%{msvc_env_include}":
escaped_include_paths,
"%{msvc_env_lib}":
escaped_lib_paths,
"%{msvc_cl_path}":
msvc_cl_path,
"%{msvc_ml_path}":
msvc_ml_path,
"%{msvc_link_path}":
msvc_link_path,
"%{msvc_lib_path}":
msvc_lib_path,
"%{cxx_builtin_include_directory}":
"\n".join(escaped_cxx_include_directories),
}
# TODO(dzc): Once these functions have been factored out of Bazel's
@ -239,6 +261,7 @@ def find_cc(repository_ctx):
" environment variable").format(target_cc_name, cc_path_envvar))
return cc
_INC_DIR_MARKER_BEGIN = "#include <...>"
# OSX add " (framework directory)" at the end of line, strip it.
@ -252,6 +275,7 @@ def _cxx_inc_convert(path):
path = path[:-_OSX_FRAMEWORK_SUFFIX_LEN].strip()
return path
def _normalize_include_path(repository_ctx, path):
"""Normalizes include paths before writing them to the crosstool.
@ -267,6 +291,7 @@ def _normalize_include_path(repository_ctx, path):
return path[len(crosstool_folder) + 1:]
return path
def _get_cxx_inc_directories_impl(repository_ctx, cc, lang_is_cpp):
"""Compute the list of default C or C++ include directories."""
if lang_is_cpp:
@ -294,6 +319,7 @@ def _get_cxx_inc_directories_impl(repository_ctx, cc, lang_is_cpp):
for p in inc_dirs.split("\n")
]
def get_cxx_inc_directories(repository_ctx, cc):
"""Compute the list of default C and C++ include directories."""
@ -305,11 +331,10 @@ def get_cxx_inc_directories(repository_ctx, cc):
includes_cpp_set = depset(includes_cpp)
return includes_cpp + [
inc
for inc in includes_c
if inc not in includes_cpp_set
inc for inc in includes_c if inc not in includes_cpp_set
]
def auto_configure_fail(msg):
"""Output failure message when cuda configuration fails."""
red = "\033[0;31m"
@ -336,6 +361,7 @@ def _host_compiler_includes(repository_ctx, cc):
inc_entries.append(" cxx_builtin_include_directory: \"%s\"" % inc_dir)
return "\n".join(inc_entries)
def _cuda_include_path(repository_ctx, cuda_config):
"""Generates the cxx_builtin_include_directory entries for cuda inc dirs.
@ -348,8 +374,7 @@ def _cuda_include_path(repository_ctx, cuda_config):
host compiler include directories, which can be added to the CROSSTOOL
file.
"""
nvcc_path = repository_ctx.path("%s/bin/nvcc%s" %
(
nvcc_path = repository_ctx.path("%s/bin/nvcc%s" % (
cuda_config.cuda_toolkit_path,
".exe" if cuda_config.cpu_value == "Windows" else "",
))
@ -363,23 +388,26 @@ def _cuda_include_path(repository_ctx, cuda_config):
target_dir = ""
for one_line in result.stderr.splitlines():
if one_line.startswith("#$ _TARGET_DIR_="):
target_dir = (cuda_config.cuda_toolkit_path + "/" +
one_line.replace("#$ _TARGET_DIR_=", "") + "/include")
target_dir = (
cuda_config.cuda_toolkit_path + "/" + one_line.replace(
"#$ _TARGET_DIR_=", "") + "/include")
inc_entries = []
if target_dir != "":
inc_entries.append(" cxx_builtin_include_directory: \"%s\"" % target_dir)
default_include = cuda_config.cuda_toolkit_path + "/include"
inc_entries.append(" cxx_builtin_include_directory: \"%s\"" %
default_include)
inc_entries.append(
" cxx_builtin_include_directory: \"%s\"" % default_include)
return "\n".join(inc_entries)
def _enable_cuda(repository_ctx):
if "TF_NEED_CUDA" in repository_ctx.os.environ:
enable_cuda = repository_ctx.os.environ["TF_NEED_CUDA"].strip()
return enable_cuda == "1"
return False
def _cuda_toolkit_path(repository_ctx):
def cuda_toolkit_path(repository_ctx):
"""Finds the cuda toolkit directory.
Args:
@ -395,6 +423,7 @@ def _cuda_toolkit_path(repository_ctx):
auto_configure_fail("Cannot find cuda toolkit path.")
return str(repository_ctx.path(cuda_toolkit_path).realpath)
def _cudnn_install_basedir(repository_ctx):
"""Finds the cudnn install directory."""
cudnn_install_path = _DEFAULT_CUDNN_INSTALL_PATH
@ -404,11 +433,14 @@ def _cudnn_install_basedir(repository_ctx):
auto_configure_fail("Cannot find cudnn install path.")
return cudnn_install_path
def matches_version(environ_version, detected_version):
"""Checks whether the user-specified version matches the detected version.
This function performs a weak matching so that if the user specifies only the
major or major and minor versions, the versions are still considered matching
This function performs a weak matching so that if the user specifies only
the
major or major and minor versions, the versions are still considered
matching
if the version parts match. To illustrate:
environ_version detected_version result
@ -424,7 +456,6 @@ def matches_version(environ_version, detected_version):
variables.
detected_version: The version autodetected from the CUDA installation on
the system.
Returns: True if user-specified version matches detected version and False
otherwise.
"""
@ -439,6 +470,7 @@ def matches_version(environ_version, detected_version):
return False
return True
_NVCC_VERSION_PREFIX = "Cuda compilation tools, release "
def _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value):
@ -453,8 +485,7 @@ def _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value):
"""
# Run nvcc --version and find the line containing the CUDA version.
nvcc_path = repository_ctx.path("%s/bin/nvcc%s" %
(
nvcc_path = repository_ctx.path("%s/bin/nvcc%s" % (
cuda_toolkit_path,
".exe" if cpu_value == "Windows" else "",
))
@ -468,8 +499,7 @@ def _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value):
if version_line.find(_NVCC_VERSION_PREFIX) == -1:
auto_configure_fail(
"Could not parse CUDA version from nvcc --version. Got: %s" %
result.stdout,
)
result.stdout,)
# Parse the CUDA version from the line containing the CUDA version.
prefix_removed = version_line.replace(_NVCC_VERSION_PREFIX, "")
@ -477,8 +507,7 @@ def _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value):
if len(parts) != 2 or len(parts[0]) < 2:
auto_configure_fail(
"Could not parse CUDA version from nvcc --version. Got: %s" %
result.stdout,
)
result.stdout,)
full_version = parts[1].strip()
if full_version.startswith("V"):
full_version = full_version[1:]
@ -491,8 +520,7 @@ def _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value):
if environ_version and not matches_version(environ_version, full_version):
auto_configure_fail(
("CUDA version detected from nvcc (%s) does not match " +
"TF_CUDA_VERSION (%s)") % (full_version, environ_version),
)
"TF_CUDA_VERSION (%s)") % (full_version, environ_version),)
# We only use the version consisting of the major and minor version numbers.
version_parts = full_version.split(".")
@ -504,6 +532,7 @@ def _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value):
version = "%s.%s" % (version_parts[0], version_parts[1])
return version
_DEFINE_CUDNN_MAJOR = "#define CUDNN_MAJOR"
_DEFINE_CUDNN_MINOR = "#define CUDNN_MINOR"
_DEFINE_CUDNN_PATCHLEVEL = "#define CUDNN_PATCHLEVEL"
@ -530,15 +559,15 @@ def find_cuda_define(repository_ctx, header_dir, header_file, define):
auto_configure_fail("Cannot find %s at %s" % (header_file, str(h_path)))
result = repository_ctx.execute(
# Grep one more lines as some #defines are splitted into two lines.
["grep", "--color=never", "-A1", "-E", define, str(h_path)],
)
["grep", "--color=never", "-A1", "-E", define,
str(h_path)],)
if result.stderr:
auto_configure_fail("Error reading %s: %s" % (str(h_path), result.stderr))
# Parse the version from the line defining the macro.
if result.stdout.find(define) == -1:
auto_configure_fail("Cannot find line containing '%s' in %s" %
(define, h_path))
auto_configure_fail(
"Cannot find line containing '%s' in %s" % (define, h_path))
# Split results to lines
lines = result.stdout.split("\n")
@ -563,11 +592,11 @@ def find_cuda_define(repository_ctx, header_dir, header_file, define):
if version_end == 0:
auto_configure_fail(
"Cannot extract the version from line containing '%s' in %s" %
(define, str(h_path)),
)
(define, str(h_path)),)
version = version[:version_end].strip()
return version
def _cudnn_version(repository_ctx, cudnn_install_basedir, cpu_value):
"""Detects the version of cuDNN installed on the system.
@ -609,13 +638,11 @@ def _cudnn_version(repository_ctx, cudnn_install_basedir, cpu_value):
if _TF_CUDNN_VERSION in repository_ctx.os.environ:
environ_version = repository_ctx.os.environ[_TF_CUDNN_VERSION].strip()
if environ_version and not matches_version(environ_version, full_version):
cudnn_h_path = repository_ctx.path("%s/include/cudnn.h" %
cudnn_install_basedir)
auto_configure_fail(
("cuDNN version detected from %s (%s) does not match " +
cudnn_h_path = repository_ctx.path(
"%s/include/cudnn.h" % cudnn_install_basedir)
auto_configure_fail(("cuDNN version detected from %s (%s) does not match " +
"TF_CUDNN_VERSION (%s)") %
(str(cudnn_h_path), full_version, environ_version),
)
(str(cudnn_h_path), full_version, environ_version),)
# We only use the major version since we use the libcudnn libraries that are
# only versioned with the major version (e.g. libcudnn.so.5).
@ -624,7 +651,8 @@ def _cudnn_version(repository_ctx, cudnn_install_basedir, cpu_value):
version = "64_" + version
return version
def _compute_capabilities(repository_ctx):
def compute_capabilities(repository_ctx):
"""Returns a list of strings representing cuda compute capabilities."""
if _TF_CUDA_COMPUTE_CAPABILITIES not in repository_ctx.os.environ:
return _DEFAULT_CUDA_COMPUTE_CAPABILITIES
@ -639,6 +667,7 @@ def _compute_capabilities(repository_ctx):
auto_configure_fail("Invalid compute capability: %s" % capability)
return capabilities
def get_cpu_value(repository_ctx):
"""Returns the name of the host operating system.
@ -656,10 +685,12 @@ def get_cpu_value(repository_ctx):
result = repository_ctx.execute(["uname", "-s"])
return result.stdout.strip()
def _is_windows(repository_ctx):
"""Returns true if the host operating system is windows."""
return get_cpu_value(repository_ctx) == "Windows"
def _lib_name(lib, cpu_value, version = "", static = False):
"""Constructs the platform-specific name of a library.
@ -690,6 +721,7 @@ def _lib_name(lib, cpu_value, version = "", static = False):
else:
auto_configure_fail("Invalid cpu_value: %s" % cpu_value)
def _find_cuda_lib(
lib,
repository_ctx,
@ -719,6 +751,7 @@ def _find_cuda_lib(
return struct(file_name=file_name, path=str(path.realpath))
auto_configure_fail("Cannot find cuda library %s" % file_name)
def _find_cupti_header_dir(repository_ctx, cuda_config):
"""Returns the path to the directory containing cupti.h
@ -734,9 +767,12 @@ def _find_cupti_header_dir(repository_ctx, cuda_config):
"""
cuda_toolkit_path = cuda_config.cuda_toolkit_path
for relative_path in CUPTI_HEADER_PATHS:
if repository_ctx.path("%s/%scupti.h" % (cuda_toolkit_path, relative_path)).exists:
if repository_ctx.path(
"%s/%scupti.h" % (cuda_toolkit_path, relative_path)).exists:
return ("%s/%s" % (cuda_toolkit_path, relative_path))[:-1]
auto_configure_fail("Cannot find cupti.h under %s" % ", ".join([cuda_toolkit_path + "/" + s for s in CUPTI_HEADER_PATHS]))
auto_configure_fail("Cannot find cupti.h under %s" % ", ".join(
[cuda_toolkit_path + "/" + s for s in CUPTI_HEADER_PATHS]))
def _find_cupti_lib(repository_ctx, cuda_config):
"""Finds the cupti library on the system.
@ -761,13 +797,13 @@ def _find_cupti_lib(repository_ctx, cuda_config):
cuda_toolkit_path = cuda_config.cuda_toolkit_path
for relative_path in CUPTI_LIB_PATHS:
path = repository_ctx.path(
"%s/%s%s" % (cuda_toolkit_path, relative_path, file_name),
)
"%s/%s%s" % (cuda_toolkit_path, relative_path, file_name),)
if path.exists:
return struct(file_name=file_name, path=str(path.realpath))
auto_configure_fail("Cannot find cupti library %s" % file_name)
def _find_libs(repository_ctx, cuda_config):
"""Returns the CUDA and cuDNN libraries on the system.
@ -780,15 +816,19 @@ def _find_libs(repository_ctx, cuda_config):
"""
cpu_value = cuda_config.cpu_value
return {
"cuda": _find_cuda_lib("cuda", repository_ctx, cpu_value, cuda_config.cuda_toolkit_path),
"cudart": _find_cuda_lib(
"cuda":
_find_cuda_lib("cuda", repository_ctx, cpu_value,
cuda_config.cuda_toolkit_path),
"cudart":
_find_cuda_lib(
"cudart",
repository_ctx,
cpu_value,
cuda_config.cuda_toolkit_path,
cuda_config.cuda_version,
),
"cudart_static": _find_cuda_lib(
"cudart_static":
_find_cuda_lib(
"cudart_static",
repository_ctx,
cpu_value,
@ -796,44 +836,51 @@ def _find_libs(repository_ctx, cuda_config):
cuda_config.cuda_version,
static=True,
),
"cublas": _find_cuda_lib(
"cublas":
_find_cuda_lib(
"cublas",
repository_ctx,
cpu_value,
cuda_config.cuda_toolkit_path,
cuda_config.cuda_version,
),
"cusolver": _find_cuda_lib(
"cusolver":
_find_cuda_lib(
"cusolver",
repository_ctx,
cpu_value,
cuda_config.cuda_toolkit_path,
cuda_config.cuda_version,
),
"curand": _find_cuda_lib(
"curand":
_find_cuda_lib(
"curand",
repository_ctx,
cpu_value,
cuda_config.cuda_toolkit_path,
cuda_config.cuda_version,
),
"cufft": _find_cuda_lib(
"cufft":
_find_cuda_lib(
"cufft",
repository_ctx,
cpu_value,
cuda_config.cuda_toolkit_path,
cuda_config.cuda_version,
),
"cudnn": _find_cuda_lib(
"cudnn":
_find_cuda_lib(
"cudnn",
repository_ctx,
cpu_value,
cuda_config.cudnn_install_basedir,
cuda_config.cudnn_version,
),
"cupti": _find_cupti_lib(repository_ctx, cuda_config),
"cupti":
_find_cupti_lib(repository_ctx, cuda_config),
}
def _find_cuda_include_path(repository_ctx, cuda_config):
"""Returns the path to the directory containing cuda.h
@ -846,10 +893,12 @@ def _find_cuda_include_path(repository_ctx, cuda_config):
"""
cuda_toolkit_path = cuda_config.cuda_toolkit_path
for relative_path in CUDA_INCLUDE_PATHS:
if repository_ctx.path("%s/%scuda.h" % (cuda_toolkit_path, relative_path)).exists:
if repository_ctx.path(
"%s/%scuda.h" % (cuda_toolkit_path, relative_path)).exists:
return ("%s/%s" % (cuda_toolkit_path, relative_path))[:-1]
auto_configure_fail("Cannot find cuda.h under %s" % cuda_toolkit_path)
def _find_cudnn_header_dir(repository_ctx, cudnn_install_basedir):
"""Returns the path to the directory containing cudnn.h
@ -862,12 +911,14 @@ def _find_cudnn_header_dir(repository_ctx, cudnn_install_basedir):
The path of the directory containing the cudnn header.
"""
for relative_path in CUDA_INCLUDE_PATHS:
if repository_ctx.path("%s/%scudnn.h" % (cudnn_install_basedir, relative_path)).exists:
if repository_ctx.path(
"%s/%scudnn.h" % (cudnn_install_basedir, relative_path)).exists:
return ("%s/%s" % (cudnn_install_basedir, relative_path))[:-1]
if repository_ctx.path("/usr/include/cudnn.h").exists:
return "/usr/include"
auto_configure_fail("Cannot find cudnn.h under %s" % cudnn_install_basedir)
def _find_nvvm_libdevice_dir(repository_ctx, cuda_config):
"""Returns the path to the directory containing libdevice in bitcode format.
@ -881,14 +932,18 @@ def _find_nvvm_libdevice_dir(repository_ctx, cuda_config):
cuda_toolkit_path = cuda_config.cuda_toolkit_path
for libdevice_file in NVVM_LIBDEVICE_FILES:
for relative_path in NVVM_LIBDEVICE_PATHS:
if repository_ctx.path("%s/%s%s" % (cuda_toolkit_path, relative_path, libdevice_file)).exists:
if repository_ctx.path("%s/%s%s" % (cuda_toolkit_path, relative_path,
libdevice_file)).exists:
return ("%s/%s" % (cuda_toolkit_path, relative_path))[:-1]
auto_configure_fail("Cannot find libdevice*.bc files under %s" % cuda_toolkit_path)
auto_configure_fail(
"Cannot find libdevice*.bc files under %s" % cuda_toolkit_path)
def _cudart_static_linkopt(cpu_value):
"""Returns additional platform-specific linkopts for cudart."""
return "" if cpu_value == "Darwin" else "\"-lrt\","
def _get_cuda_config(repository_ctx):
"""Detects and returns information about the CUDA installation on the system.
@ -905,19 +960,21 @@ def _get_cuda_config(repository_ctx):
cpu_value: The name of the host operating system.
"""
cpu_value = get_cpu_value(repository_ctx)
cuda_toolkit_path = _cuda_toolkit_path(repository_ctx)
cuda_version = _cuda_version(repository_ctx, cuda_toolkit_path, cpu_value)
toolkit_path = cuda_toolkit_path(repository_ctx)
cuda_version = _cuda_version(repository_ctx, toolkit_path, cpu_value)
cudnn_install_basedir = _cudnn_install_basedir(repository_ctx)
cudnn_version = _cudnn_version(repository_ctx, cudnn_install_basedir, cpu_value)
cudnn_version = _cudnn_version(repository_ctx, cudnn_install_basedir,
cpu_value)
return struct(
cuda_toolkit_path = cuda_toolkit_path,
cuda_toolkit_path=toolkit_path,
cudnn_install_basedir=cudnn_install_basedir,
cuda_version=cuda_version,
cudnn_version=cudnn_version,
compute_capabilities = _compute_capabilities(repository_ctx),
compute_capabilities=compute_capabilities(repository_ctx),
cpu_value=cpu_value,
)
def _tpl(repository_ctx, tpl, substitutions = {}, out = None):
if not out:
out = tpl.replace(":", "/")
@ -927,6 +984,7 @@ def _tpl(repository_ctx, tpl, substitutions = {}, out = None):
substitutions,
)
def _file(repository_ctx, label):
repository_ctx.template(
label.replace(":", "/"),
@ -934,6 +992,7 @@ def _file(repository_ctx, label):
{},
)
_DUMMY_CROSSTOOL_BZL_FILE = """
def error_gpu_disabled():
fail("ERROR: Building with --config=cuda but TensorFlow is not configured " +
@ -975,22 +1034,34 @@ def _create_dummy_repository(repository_ctx):
repository_ctx,
"cuda:BUILD",
{
"%{cuda_driver_lib}": _lib_name("cuda", cpu_value),
"%{cudart_static_lib}": _lib_name(
"%{cuda_driver_lib}":
_lib_name("cuda", cpu_value),
"%{cudart_static_lib}":
_lib_name(
"cudart_static",
cpu_value,
static=True,
),
"%{cudart_static_linkopt}": _cudart_static_linkopt(cpu_value),
"%{cudart_lib}": _lib_name("cudart", cpu_value),
"%{cublas_lib}": _lib_name("cublas", cpu_value),
"%{cusolver_lib}": _lib_name("cusolver", cpu_value),
"%{cudnn_lib}": _lib_name("cudnn", cpu_value),
"%{cufft_lib}": _lib_name("cufft", cpu_value),
"%{curand_lib}": _lib_name("curand", cpu_value),
"%{cupti_lib}": _lib_name("cupti", cpu_value),
"%{cuda_include_genrules}": "",
"%{cuda_headers}": "",
"%{cudart_static_linkopt}":
_cudart_static_linkopt(cpu_value),
"%{cudart_lib}":
_lib_name("cudart", cpu_value),
"%{cublas_lib}":
_lib_name("cublas", cpu_value),
"%{cusolver_lib}":
_lib_name("cusolver", cpu_value),
"%{cudnn_lib}":
_lib_name("cudnn", cpu_value),
"%{cufft_lib}":
_lib_name("cufft", cpu_value),
"%{curand_lib}":
_lib_name("curand", cpu_value),
"%{cupti_lib}":
_lib_name("cupti", cpu_value),
"%{cuda_include_genrules}":
"",
"%{cuda_headers}":
"",
},
)
@ -1002,7 +1073,8 @@ def _create_dummy_repository(repository_ctx):
repository_ctx.file("cuda/cuda/extras/CUPTI/include/cupti.h", "")
repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cuda", cpu_value))
repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cudart", cpu_value))
repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cudart_static", cpu_value))
repository_ctx.file(
"cuda/cuda/lib/%s" % _lib_name("cudart_static", cpu_value))
repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cublas", cpu_value))
repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cusolver", cpu_value))
repository_ctx.file("cuda/cuda/lib/%s" % _lib_name("cudnn", cpu_value))
@ -1016,13 +1088,17 @@ def _create_dummy_repository(repository_ctx):
repository_ctx,
"cuda:cuda_config.h",
{
"%{cuda_version}": _DEFAULT_CUDA_VERSION,
"%{cudnn_version}": _DEFAULT_CUDNN_VERSION,
"%{cuda_compute_capabilities}": ",".join([
"%{cuda_version}":
_DEFAULT_CUDA_VERSION,
"%{cudnn_version}":
_DEFAULT_CUDNN_VERSION,
"%{cuda_compute_capabilities}":
",".join([
"CudaVersion(\"%s\")" % c
for c in _DEFAULT_CUDA_COMPUTE_CAPABILITIES
]),
"%{cuda_toolkit_path}": _DEFAULT_CUDA_TOOLKIT_PATH,
"%{cuda_toolkit_path}":
_DEFAULT_CUDA_TOOLKIT_PATH,
},
"cuda/cuda/cuda_config.h",
)
@ -1036,6 +1112,7 @@ def _create_dummy_repository(repository_ctx):
)
repository_ctx.file("crosstool/BUILD", _DUMMY_CROSSTOOL_BUILD_FILE)
def _execute(
repository_ctx,
cmdline,
@ -1049,10 +1126,9 @@ def _execute(
cmdline: list of strings, the command to execute
error_msg: string, a summary of the error if the command fails
error_details: string, details about the error or steps to fix it
empty_stdout_fine: bool, if True, an empty stdout result is fine, otherwise
it's an error
Return:
the result of repository_ctx.execute(cmdline)
empty_stdout_fine: bool, if True, an empty stdout result is fine,
otherwise it's an error
Return: the result of repository_ctx.execute(cmdline)
"""
result = repository_ctx.execute(cmdline)
if result.stderr or not (empty_stdout_fine or result.stdout):
@ -1061,10 +1137,10 @@ def _execute(
error_msg.strip() if error_msg else "Repository command failed",
result.stderr.strip(),
error_details if error_details else "",
]),
)
]),)
return result
def _norm_path(path):
"""Returns a path with '/' and remove the trailing slash."""
path = path.replace("\\", "/")
@ -1072,6 +1148,7 @@ def _norm_path(path):
path = path[:-1]
return path
def symlink_genrule_for_dir(
repository_ctx,
src_dir,
@ -1105,7 +1182,8 @@ def symlink_genrule_for_dir(
if dest_files[i] != "":
# If we have only one file to link we do not want to use the dest_dir, as
# $(@D) will include the full path to the file.
dest = "$(@D)/" + dest_dir + dest_files[i] if len(dest_files) != 1 else "$(@D)/" + dest_files[i]
dest = "$(@D)/" + dest_dir + dest_files[i] if len(
dest_files) != 1 else "$(@D)/" + dest_files[i]
# Copy the headers to create a sandboxable setup.
cmd = "cp -f"
@ -1119,23 +1197,16 @@ def symlink_genrule_for_dir(
)
return genrule
def _genrule(src_dir, genrule_name, command, outs):
"""Returns a string with a genrule.
Genrule executes the given command and produces the given outputs.
"""
return (
"genrule(\n" +
' name = "' +
genrule_name + '",\n' +
" outs = [\n" +
outs +
"\n ],\n" +
' cmd = """\n' +
command +
'\n """,\n' +
")\n"
)
"genrule(\n" + ' name = "' + genrule_name + '",\n' + " outs = [\n" +
outs + "\n ],\n" + ' cmd = """\n' + command + '\n """,\n' + ")\n")
def _read_dir(repository_ctx, src_dir):
"""Returns a string with all files in a directory.
@ -1164,24 +1235,31 @@ def _read_dir(repository_ctx, src_dir):
result = find_result.stdout
return result
def _flag_enabled(repository_ctx, flag_name):
if flag_name in repository_ctx.os.environ:
value = repository_ctx.os.environ[flag_name].strip()
return value == "1"
return False
def _use_cuda_clang(repository_ctx):
return _flag_enabled(repository_ctx, "TF_CUDA_CLANG")
def _compute_cuda_extra_copts(repository_ctx, compute_capabilities):
if _use_cuda_clang(repository_ctx):
capability_flags = ["--cuda-gpu-arch=sm_" +
cap.replace(".", "") for cap in compute_capabilities]
capability_flags = [
"--cuda-gpu-arch=sm_" + cap.replace(".", "")
for cap in compute_capabilities
]
else:
# Capabilities are handled in the "crosstool_wrapper_driver_is_not_gcc" for nvcc
# TODO(csigg): Make this consistent with cuda clang and pass to crosstool.
capability_flags = []
return str(capability_flags)
def _create_local_cuda_repository(repository_ctx):
"""Creates the repository containing files set up to build with CUDA."""
cuda_config = _get_cuda_config(repository_ctx)
@ -1198,19 +1276,23 @@ def _create_local_cuda_repository(repository_ctx):
# symlinking. We create one genrule for each directory we want to track under
# cuda_toolkit_path
cuda_toolkit_path = cuda_config.cuda_toolkit_path
genrules = [symlink_genrule_for_dir(
genrules = [
symlink_genrule_for_dir(
repository_ctx,
cuda_include_path,
"cuda/include",
"cuda-include",
)]
genrules.append(symlink_genrule_for_dir(
)
]
genrules.append(
symlink_genrule_for_dir(
repository_ctx,
nvvm_libdevice_dir,
"cuda/nvvm/libdevice",
"cuda-nvvm",
))
genrules.append(symlink_genrule_for_dir(
genrules.append(
symlink_genrule_for_dir(
repository_ctx,
cupti_header_dir,
"cuda/extras/CUPTI/include",
@ -1223,7 +1305,8 @@ def _create_local_cuda_repository(repository_ctx):
for lib in cuda_libs.values():
cuda_lib_src.append(lib.path)
cuda_lib_dest.append("cuda/lib/" + lib.file_name)
genrules.append(symlink_genrule_for_dir(
genrules.append(
symlink_genrule_for_dir(
repository_ctx,
None,
"",
@ -1239,7 +1322,8 @@ def _create_local_cuda_repository(repository_ctx):
"",
).splitlines()
if "/cudnn.h" not in included_files:
genrules.append(symlink_genrule_for_dir(
genrules.append(
symlink_genrule_for_dir(
repository_ctx,
None,
"cuda/include/",
@ -1249,19 +1333,18 @@ def _create_local_cuda_repository(repository_ctx):
))
else:
genrules.append(
"filegroup(\n" +
' name = "cudnn-include",\n' +
" srcs = [],\n" +
")\n",
)
"filegroup(\n" + ' name = "cudnn-include",\n' + " srcs = [],\n" +
")\n",)
# Set up BUILD file for cuda/
_tpl(
repository_ctx,
"cuda:build_defs.bzl",
{
"%{cuda_is_configured}": "True",
"%{cuda_extra_copts}": _compute_cuda_extra_copts(
"%{cuda_is_configured}":
"True",
"%{cuda_extra_copts}":
_compute_cuda_extra_copts(
repository_ctx,
cuda_config.compute_capabilities,
),
@ -1271,21 +1354,30 @@ def _create_local_cuda_repository(repository_ctx):
repository_ctx,
"cuda:BUILD.windows" if _is_windows(repository_ctx) else "cuda:BUILD",
{
"%{cuda_driver_lib}": cuda_libs["cuda"].file_name,
"%{cudart_static_lib}": cuda_libs["cudart_static"].file_name,
"%{cudart_static_linkopt}": _cudart_static_linkopt(
cuda_config.cpu_value,
"%{cuda_driver_lib}":
cuda_libs["cuda"].file_name,
"%{cudart_static_lib}":
cuda_libs["cudart_static"].file_name,
"%{cudart_static_linkopt}":
_cudart_static_linkopt(cuda_config.cpu_value,),
"%{cudart_lib}":
cuda_libs["cudart"].file_name,
"%{cublas_lib}":
cuda_libs["cublas"].file_name,
"%{cusolver_lib}":
cuda_libs["cusolver"].file_name,
"%{cudnn_lib}":
cuda_libs["cudnn"].file_name,
"%{cufft_lib}":
cuda_libs["cufft"].file_name,
"%{curand_lib}":
cuda_libs["curand"].file_name,
"%{cupti_lib}":
cuda_libs["cupti"].file_name,
"%{cuda_include_genrules}":
"\n".join(genrules),
"%{cuda_headers}": ('":cuda-include",\n' + ' ":cudnn-include",'
),
"%{cudart_lib}": cuda_libs["cudart"].file_name,
"%{cublas_lib}": cuda_libs["cublas"].file_name,
"%{cusolver_lib}": cuda_libs["cusolver"].file_name,
"%{cudnn_lib}": cuda_libs["cudnn"].file_name,
"%{cufft_lib}": cuda_libs["cufft"].file_name,
"%{curand_lib}": cuda_libs["curand"].file_name,
"%{cupti_lib}": cuda_libs["cupti"].file_name,
"%{cuda_include_genrules}": "\n".join(genrules),
"%{cuda_headers}": ('":cuda-include",\n' +
' ":cudnn-include",'),
},
"cuda/BUILD",
)
@ -1326,24 +1418,29 @@ def _create_local_cuda_repository(repository_ctx):
flag: "-Wno-invalid-partial-specialization"
"""
cuda_defines["%{host_compiler_includes}"] = host_compiler_includes
_tpl(repository_ctx, "crosstool:BUILD", {"%{linker_files}": ":empty", "%{win_linker_files}": ":empty"})
repository_ctx.file("crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc", "")
_tpl(repository_ctx, "crosstool:BUILD", {
"%{linker_files}": ":empty",
"%{win_linker_files}": ":empty"
})
repository_ctx.file(
"crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc", "")
repository_ctx.file("crosstool/windows/msvc_wrapper_for_nvcc.py", "")
repository_ctx.file("crosstool/windows/msvc_wrapper_for_nvcc.bat", "")
else:
cuda_defines["%{host_compiler_path}"] = "clang/bin/crosstool_wrapper_driver_is_not_gcc"
cuda_defines[
"%{host_compiler_path}"] = "clang/bin/crosstool_wrapper_driver_is_not_gcc"
cuda_defines["%{host_compiler_warnings}"] = ""
# nvcc has the system include paths built in and will automatically
# search them; we cannot work around that, so we add the relevant cuda
# system paths to the allowed compiler specific include paths.
cuda_defines["%{host_compiler_includes}"] = (
host_compiler_includes + "\n" +
_cuda_include_path(repository_ctx, cuda_config) +
host_compiler_includes + "\n" + _cuda_include_path(
repository_ctx, cuda_config) +
"\n cxx_builtin_include_directory: \"%s\"" % cupti_header_dir +
"\n cxx_builtin_include_directory: \"%s\"" % cudnn_header_dir)
nvcc_path = str(repository_ctx.path("%s/bin/nvcc%s" %
(
nvcc_path = str(
repository_ctx.path("%s/bin/nvcc%s" % (
cuda_config.cuda_toolkit_path,
".exe" if _is_windows(repository_ctx) else "",
)))
@ -1356,14 +1453,19 @@ def _create_local_cuda_repository(repository_ctx):
},
)
wrapper_defines = {
"%{cpu_compiler}": str(cc),
"%{cuda_version}": cuda_config.cuda_version,
"%{nvcc_path}": nvcc_path,
"%{gcc_host_compiler_path}": str(cc),
"%{cuda_compute_capabilities}": ", ".join(
["\"%s\"" % c for c in cuda_config.compute_capabilities],
),
"%{nvcc_tmp_dir}": _get_nvcc_tmp_dir_for_windows(repository_ctx),
"%{cpu_compiler}":
str(cc),
"%{cuda_version}":
cuda_config.cuda_version,
"%{nvcc_path}":
nvcc_path,
"%{gcc_host_compiler_path}":
str(cc),
"%{cuda_compute_capabilities}":
", ".join(
["\"%s\"" % c for c in cuda_config.compute_capabilities],),
"%{nvcc_tmp_dir}":
_get_nvcc_tmp_dir_for_windows(repository_ctx),
}
_tpl(
repository_ctx,
@ -1396,29 +1498,34 @@ def _create_local_cuda_repository(repository_ctx):
repository_ctx,
"cuda:cuda_config.h",
{
"%{cuda_version}": cuda_config.cuda_version,
"%{cudnn_version}": cuda_config.cudnn_version,
"%{cuda_compute_capabilities}": ",".join(
[
"%{cuda_version}":
cuda_config.cuda_version,
"%{cudnn_version}":
cuda_config.cudnn_version,
"%{cuda_compute_capabilities}":
",".join([
"CudaVersion(\"%s\")" % c
for c in cuda_config.compute_capabilities
],
),
"%{cuda_toolkit_path}": cuda_config.cuda_toolkit_path,
],),
"%{cuda_toolkit_path}":
cuda_config.cuda_toolkit_path,
},
"cuda/cuda/cuda_config.h",
)
def _create_remote_cuda_repository(repository_ctx, remote_config_repo):
"""Creates pointers to a remotely configured repo set up to build with CUDA."""
_tpl(
repository_ctx,
"cuda:build_defs.bzl",
{
"%{cuda_is_configured}": "True",
"%{cuda_extra_copts}": _compute_cuda_extra_copts(
"%{cuda_is_configured}":
"True",
"%{cuda_extra_copts}":
_compute_cuda_extra_copts(
repository_ctx,
_compute_capabilities(repository_ctx),
compute_capabilities(repository_ctx),
),
},
)
@ -1434,6 +1541,7 @@ def _create_remote_cuda_repository(repository_ctx, remote_config_repo):
"%{remote_cuda_repo}": remote_config_repo,
}, "crosstool/BUILD")
def _cuda_autoconf_impl(repository_ctx):
"""Implementation of the cuda_autoconf repository rule."""
if not _enable_cuda(repository_ctx):
@ -1446,6 +1554,7 @@ def _cuda_autoconf_impl(repository_ctx):
else:
_create_local_cuda_repository(repository_ctx)
cuda_configure = repository_rule(
implementation = _cuda_autoconf_impl,
environ = [

225
third_party/nccl/LICENSE vendored
View File

@ -1,203 +1,30 @@
Copyright 2018 The TensorFlow Authors. All rights reserved.
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
Copyright (c) 2015-2018, NVIDIA CORPORATION. All rights reserved.
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of NVIDIA CORPORATION, Lawrence Berkeley National
Laboratory, the U.S. Department of Energy, nor the names of their
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
1. Definitions.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
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"You" (or "Your") shall mean an individual or Legal Entity
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"Work" shall mean the work of authorship, whether in Source or
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179
third_party/nccl/archive.BUILD vendored Normal file
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@ -0,0 +1,179 @@
# NVIDIA NCCL 2
# A package of optimized primitives for collective multi-GPU communication.
licenses(["restricted"])
exports_files(["LICENSE.txt"])
load(
"@local_config_nccl//:build_defs.bzl",
"device_link",
"gen_nccl_h",
"nccl_library",
"rdc_copts",
)
load(
"@local_config_cuda//cuda:build_defs.bzl",
"cuda_default_copts",
)
# Generate the nccl.h header file.
gen_nccl_h(
name = "nccl_h",
output = "src/nccl.h",
template = "src/nccl.h.in",
)
nccl_library(
name = "src_hdrs",
hdrs = [
"src/nccl.h",
# src/include/common_coll.h #includes "collectives/collectives.h".
# All other #includes of collectives.h are patched in process_srcs.
"src/collectives/collectives.h",
],
strip_include_prefix = "src",
)
nccl_library(
name = "include_hdrs",
hdrs = glob(["src/include/*.h"]),
strip_include_prefix = "src/include",
)
filegroup(
name = "device_hdrs",
srcs = glob(["src/collectives/device/*.h"]),
)
filegroup(
name = "device_srcs",
srcs = [
"src/collectives/device/all_gather.cu",
"src/collectives/device/all_reduce.cu",
"src/collectives/device/broadcast.cu",
"src/collectives/device/reduce.cu",
"src/collectives/device/reduce_scatter.cu",
],
)
nccl_library(
name = "sum",
srcs = [
":device_hdrs",
":device_srcs",
],
copts = ["-DNCCL_OP=0"] + rdc_copts(),
prefix = "sum_",
deps = [
":src_hdrs",
":include_hdrs",
"@local_config_cuda//cuda:cuda_headers",
],
linkstatic = True,
)
nccl_library(
name = "prod",
srcs = [
":device_hdrs",
":device_srcs",
],
copts = ["-DNCCL_OP=1"] + rdc_copts(),
prefix = "_prod",
deps = [
":src_hdrs",
":include_hdrs",
"@local_config_cuda//cuda:cuda_headers",
],
linkstatic = True,
)
nccl_library(
name = "min",
srcs = [
":device_hdrs",
":device_srcs",
],
copts = ["-DNCCL_OP=2"] + rdc_copts(),
prefix = "min_",
deps = [
":src_hdrs",
":include_hdrs",
"@local_config_cuda//cuda:cuda_headers",
],
linkstatic = True,
)
nccl_library(
name = "max",
srcs = [
":device_hdrs",
":device_srcs",
],
copts = ["-DNCCL_OP=3"] + rdc_copts(),
prefix = "max_",
deps = [
":src_hdrs",
":include_hdrs",
"@local_config_cuda//cuda:cuda_headers",
],
linkstatic = True,
)
nccl_library(
name = "functions",
srcs = [
":device_hdrs",
"src/collectives/device/functions.cu",
],
copts = rdc_copts(),
deps = [
":src_hdrs",
":include_hdrs",
"@local_config_cuda//cuda:cuda_headers",
],
linkstatic = True,
)
device_link(
name = "device_code",
srcs = [
":functions",
":max",
":min",
":prod",
":sum",
],
)
# Primary NCCL target.
nccl_library(
name = "nccl",
srcs = glob(
include = ["src/**/*.cu"],
# Exclude device-library code.
exclude = ["src/collectives/device/**"],
) + [
# Required for header inclusion checking (see
# http://docs.bazel.build/versions/master/be/c-cpp.html#hdrs).
# Files in src/ which #include "nccl.h" load it from there rather than
# from the virtual includes directory.
"src/nccl.h",
],
hdrs = ["src/nccl.h"],
include_prefix = "third_party/nccl",
strip_include_prefix = "src",
copts = cuda_default_copts(),
deps = [
":device_code",
":functions",
":include_hdrs",
":max",
":min",
":prod",
":src_hdrs",
":sum",
],
visibility = ["//visibility:public"],
)

210
third_party/nccl/build_defs.bzl.tpl vendored Normal file
View File

@ -0,0 +1,210 @@
"""Repository rule for NCCL."""
load("@local_config_cuda//cuda:build_defs.bzl", "cuda_default_copts")
def _gen_nccl_h_impl(ctx):
"""Creates nccl.h from a template."""
ctx.actions.expand_template(
output = ctx.outputs.output,
template = ctx.file.template,
substitutions = {
"${nccl:Major}": "2",
"${nccl:Minor}": "3",
"${nccl:Patch}": "5",
"${nccl:Suffix}": "",
"${nccl:Version}": "2305",
},
)
gen_nccl_h = rule(
implementation = _gen_nccl_h_impl,
attrs = {
"template": attr.label(allow_single_file = True),
"output": attr.output(),
},
)
"""Creates the NCCL header file."""
def _process_srcs_impl(ctx):
"""Appends .cc to .cu files, patches include directives."""
files = []
for src in ctx.files.srcs:
if not src.is_source:
# Process only once, specifically "src/nccl.h".
files.append(src)
continue
name = src.basename
if src.extension == "cu":
name = ctx.attr.prefix + name + ".cc"
file = ctx.actions.declare_file(name, sibling = src)
ctx.actions.expand_template(
output = file,
template = src,
substitutions = {
"\"collectives.h": "\"collectives/collectives.h",
"\"../collectives.h": "\"collectives/collectives.h",
"#if __CUDACC_VER_MAJOR__":
"#if defined __CUDACC_VER_MAJOR__ && __CUDACC_VER_MAJOR__",
# Substitutions are applied in order.
"std::nullptr_t": "nullptr_t",
"nullptr_t": "std::nullptr_t",
},
)
files.append(file)
return [DefaultInfo(files = depset(files))]
_process_srcs = rule(
implementation = _process_srcs_impl,
attrs = {
"srcs": attr.label_list(allow_files = True),
"prefix": attr.string(default = ""),
},
)
"""Processes the NCCL srcs so they can be compiled with bazel and clang."""
def nccl_library(name, srcs=None, hdrs=None, prefix=None, **kwargs):
"""Processes the srcs and hdrs and creates a cc_library."""
_process_srcs(
name = name + "_srcs",
srcs = srcs,
prefix = prefix,
)
_process_srcs(
name = name + "_hdrs",
srcs = hdrs,
)
native.cc_library(
name = name,
srcs = [name + "_srcs"] if srcs else [],
hdrs = [name + "_hdrs"] if hdrs else [],
**kwargs
)
def rdc_copts():
"""Returns copts for compiling relocatable device code."""
# The global functions can not have a lower register count than the
# device functions. This is enforced by setting a fixed register count.
# https://github.com/NVIDIA/nccl/blob/f93fe9bfd94884cec2ba711897222e0df5569a53/makefiles/common.mk#L48
maxrregcount = "-maxrregcount=96"
return cuda_default_copts() + select({
"@local_config_cuda//cuda:using_nvcc": [
"-nvcc_options",
"relocatable-device-code=true",
"-nvcc_options",
"ptxas-options=" + maxrregcount,
],
"@local_config_cuda//cuda:using_clang": [
"-fcuda-rdc",
"-Xcuda-ptxas",
maxrregcount,
],
"//conditions:default": [],
}) + ["-fvisibility=hidden"]
def _filter_impl(ctx):
suffix = ctx.attr.suffix
files = [src for src in ctx.files.srcs if src.path.endswith(suffix)]
return [DefaultInfo(files = depset(files))]
_filter = rule(
implementation = _filter_impl,
attrs = {
"srcs": attr.label_list(allow_files = True),
"suffix": attr.string(),
},
)
"""Filters the srcs to the ones ending with suffix."""
def _gen_link_src_impl(ctx):
ctx.actions.expand_template(
output = ctx.outputs.output,
template = ctx.file.template,
substitutions = {
"REGISTERLINKBINARYFILE": '"%s"' % ctx.file.register_hdr.short_path,
"FATBINFILE": '"%s"' % ctx.file.fatbin_hdr.short_path,
},
)
_gen_link_src = rule(
implementation = _gen_link_src_impl,
attrs = {
"register_hdr": attr.label(allow_single_file = True),
"fatbin_hdr": attr.label(allow_single_file = True),
"template": attr.label(allow_single_file = True),
"output": attr.output(),
},
)
"""Patches the include directives for the link.stub file."""
def device_link(name, srcs):
"""Links seperately compiled relocatable device code into a cc_library."""
# From .a and .pic.a archives, just use the latter.
_filter(
name = name + "_pic_a",
srcs = srcs,
suffix = ".pic.a",
)
# Device-link to cubins for each architecture.
images = []
cubins = []
for arch in %{gpu_architectures}:
cubin = "%s_%s.cubin" % (name, arch)
register_hdr = "%s_%s.h" % (name, arch)
nvlink = "@local_config_nccl//:nvlink"
cmd = ("$(location %s) --cpu-arch=X86_64 " % nvlink +
"--arch=%s $(SRCS) " % arch +
"--register-link-binaries=$(location %s) " % register_hdr +
"--output-file=$(location %s)" % cubin)
native.genrule(
name = "%s_%s" % (name, arch),
outs = [register_hdr, cubin],
srcs = [name + "_pic_a"],
cmd = cmd,
tools = [nvlink],
)
images.append("--image=profile=%s,file=$(location %s)" % (arch, cubin))
cubins.append(cubin)
# Generate fatbin header from all cubins.
fatbin_hdr = name + ".fatbin.h"
fatbinary = "@local_config_nccl//:cuda/bin/fatbinary"
cmd = ("PATH=$$CUDA_TOOLKIT_PATH/bin:$$PATH " + # for bin2c
"$(location %s) -64 --cmdline=--compile-only --link " % fatbinary +
"--compress-all %s --create=%%{name}.fatbin " % " ".join(images) +
"--embedded-fatbin=$@")
native.genrule(
name = name + "_fatbin_h",
outs = [fatbin_hdr],
srcs = cubins,
cmd = cmd,
tools = [fatbinary],
)
# Generate the source file #including the headers generated above.
_gen_link_src(
name = name + "_cc",
# Include just the last one, they are equivalent.
register_hdr = register_hdr,
fatbin_hdr = fatbin_hdr,
template = "@local_config_nccl//:cuda/bin/crt/link.stub",
output = name + ".cc",
)
# Compile the source file into the cc_library.
native.cc_library(
name = name,
srcs = [name + "_cc"],
textual_hdrs = [register_hdr, fatbin_hdr],
deps = [
"@local_config_cuda//cuda:cuda_headers",
"@local_config_cuda//cuda:cudart_static",
],
)

68
third_party/nccl/nccl_archive.BUILD vendored
View File

@ -1,68 +0,0 @@
# NVIDIA nccl
# A package of optimized primitives for collective multi-GPU communication.
licenses(["notice"]) # BSD
exports_files(["LICENSE.txt"])
load("@local_config_cuda//cuda:build_defs.bzl", "cuda_default_copts", "if_cuda")
SRCS = [
"src/all_gather.cu",
"src/all_reduce.cu",
"src/broadcast.cu",
"src/core.cu",
"src/libwrap.cu",
"src/reduce.cu",
"src/reduce_scatter.cu",
]
# Copy .cu to .cu.cc so they can be in srcs of cc_library.
[
genrule(
name = "gen_" + src,
srcs = [src],
outs = [src + ".cc"],
cmd = "cp $(location " + src + ") $(location " + src + ".cc)",
)
for src in SRCS
]
SRCS_CU_CC = [src + ".cc" for src in SRCS]
cc_library(
name = "nccl",
srcs = if_cuda(SRCS_CU_CC + glob(["src/*.h"])),
hdrs = if_cuda(["src/nccl.h"]),
copts = [
"-DCUDA_MAJOR=0",
"-DCUDA_MINOR=0",
"-DNCCL_MAJOR=0",
"-DNCCL_MINOR=0",
"-DNCCL_PATCH=0",
"-Iexternal/nccl_archive/src",
"-O3",
] + cuda_default_copts(),
include_prefix = "third_party/nccl",
linkopts = select({
"@org_tensorflow//tensorflow:android": [
"-pie",
],
"@org_tensorflow//tensorflow:darwin": [
"-Wl,-framework",
"-Wl,CoreFoundation",
"-Wl,-framework",
"-Wl,Security",
],
"@org_tensorflow//tensorflow:ios": [],
"@org_tensorflow//tensorflow:windows": [
"-DEFAULTLIB:ws2_32.lib",
],
"//conditions:default": [
"-lrt",
],
}),
strip_include_prefix = "src",
visibility = ["//visibility:public"],
deps = ["@local_config_cuda//cuda:cuda_headers"],
)

104
third_party/nccl/nccl_configure.bzl vendored
View File

@ -11,12 +11,16 @@
load(
"//third_party/gpus:cuda_configure.bzl",
"auto_configure_fail",
"compute_capabilities",
"cuda_toolkit_path",
"find_cuda_define",
"matches_version",
)
_NCCL_INSTALL_PATH = "NCCL_INSTALL_PATH"
_CUDA_TOOLKIT_PATH = "CUDA_TOOLKIT_PATH"
_NCCL_HDR_PATH = "NCCL_HDR_PATH"
_NCCL_INSTALL_PATH = "NCCL_INSTALL_PATH"
_TF_CUDA_COMPUTE_CAPABILITIES = "TF_CUDA_COMPUTE_CAPABILITIES"
_TF_NCCL_VERSION = "TF_NCCL_VERSION"
_TF_NCCL_CONFIG_REPO = "TF_NCCL_CONFIG_REPO"
@ -37,6 +41,12 @@ cc_library(
"""
_NCCL_ARCHIVE_BUILD_CONTENT = """
exports_files([
"cuda/bin/crt/link.stub",
"cuda/bin/fatbinary",
"nvlink",
])
filegroup(
name = "LICENSE",
data = ["@nccl_archive//:LICENSE.txt"],
@ -50,9 +60,8 @@ alias(
)
"""
# Local build results in dynamic link and the license should not be included.
_NCCL_REMOTE_BUILD_TEMPLATE = Label("//third_party/nccl:remote.BUILD.tpl")
_NCCL_LOCAL_BUILD_TEMPLATE = Label("//third_party/nccl:system.BUILD.tpl")
def _label(file):
return Label("//third_party/nccl:{}".format(file))
def _find_nccl_header(repository_ctx, nccl_install_path):
"""Finds the NCCL header on the system.
@ -69,13 +78,13 @@ def _find_nccl_header(repository_ctx, nccl_install_path):
auto_configure_fail("Cannot find %s" % str(header_path))
return header_path
def _check_nccl_version(repository_ctx, nccl_install_path, nccl_hdr_path, nccl_version):
"""Checks whether the header file matches the specified version of NCCL.
Args:
repository_ctx: The repository context.
nccl_install_path: The NCCL library install directory.
nccl_hdr_path: The NCCL header path.
nccl_version: The expected NCCL version.
Returns:
@ -85,38 +94,31 @@ def _check_nccl_version(repository_ctx, nccl_install_path, nccl_hdr_path, nccl_v
if not header_path.exists:
header_path = _find_nccl_header(repository_ctx, nccl_install_path)
header_dir = str(header_path.realpath.dirname)
major_version = find_cuda_define(repository_ctx, header_dir, "nccl.h",
_DEFINE_NCCL_MAJOR)
minor_version = find_cuda_define(repository_ctx, header_dir, "nccl.h",
_DEFINE_NCCL_MINOR)
patch_version = find_cuda_define(repository_ctx, header_dir, "nccl.h",
_DEFINE_NCCL_PATCH)
major_version = find_cuda_define(
repository_ctx,
header_dir,
"nccl.h",
_DEFINE_NCCL_MAJOR,
)
minor_version = find_cuda_define(
repository_ctx,
header_dir,
"nccl.h",
_DEFINE_NCCL_MINOR,
)
patch_version = find_cuda_define(
repository_ctx,
header_dir,
"nccl.h",
_DEFINE_NCCL_PATCH,
)
header_version = "%s.%s.%s" % (major_version, minor_version, patch_version)
if not matches_version(nccl_version, header_version):
auto_configure_fail(
("NCCL library version detected from %s/nccl.h (%s) does not match " +
"TF_NCCL_VERSION (%s). To fix this rerun configure again.") %
(header_dir, header_version, nccl_version))
def _find_nccl_lib(repository_ctx, nccl_install_path, nccl_version):
"""Finds the given NCCL library on the system.
Args:
repository_ctx: The repository context.
nccl_install_path: The NCCL library installation directory.
nccl_version: The version of NCCL library files as returned
by _nccl_version.
Returns:
The path to the NCCL library.
"""
lib_path = repository_ctx.path("%s/lib/libnccl.so.%s" % (nccl_install_path,
nccl_version))
if not lib_path.exists:
auto_configure_fail("Cannot find NCCL library %s" % str(lib_path))
return lib_path
(header_dir, header_version, nccl_version),
)
def _nccl_configure_impl(repository_ctx):
"""Implementation of the nccl_configure repository rule."""
@ -127,36 +129,56 @@ def _nccl_configure_impl(repository_ctx):
if _TF_NCCL_CONFIG_REPO in repository_ctx.os.environ:
# Forward to the pre-configured remote repository.
repository_ctx.template("BUILD", _NCCL_REMOTE_BUILD_TEMPLATE, {
repository_ctx.template("BUILD", _label("remote.BUILD.tpl"), {
"%{target}": repository_ctx.os.environ[_TF_NCCL_CONFIG_REPO],
})
return
nccl_version = repository_ctx.os.environ[_TF_NCCL_VERSION].strip()
if matches_version("1", nccl_version):
# Alias to GitHub target from @nccl_archive.
if not matches_version(nccl_version, "1.3"):
auto_configure_fail(
"NCCL from GitHub must use version 1.3 (got %s)" % nccl_version)
if nccl_version == "":
# Alias to open source build from @nccl_archive.
repository_ctx.file("BUILD", _NCCL_ARCHIVE_BUILD_CONTENT)
# TODO(csigg): implement and reuse in cuda_configure.bzl.
gpu_architectures = [
"sm_" + capability.replace(".", "")
for capability in compute_capabilities(repository_ctx)
]
# Round-about way to make the list unique.
gpu_architectures = dict(zip(gpu_architectures, gpu_architectures)).keys()
repository_ctx.template("build_defs.bzl", _label("build_defs.bzl.tpl"), {
"%{gpu_architectures}": str(gpu_architectures),
})
repository_ctx.symlink(cuda_toolkit_path(repository_ctx), "cuda")
# Temporary work-around for setups which symlink ptxas to a newer
# version. The versions of nvlink and ptxas need to agree, so we find
# nvlink next to the real location of ptxas. This is only temporary and
# will be removed again soon.
nvlink_dir = repository_ctx.path("cuda/bin/ptxas").realpath.dirname
repository_ctx.symlink(nvlink_dir.get_child("nvlink"), "nvlink")
else:
# Create target for locally installed NCCL.
nccl_install_path = repository_ctx.os.environ[_NCCL_INSTALL_PATH].strip()
nccl_hdr_path = repository_ctx.os.environ[_NCCL_HDR_PATH].strip()
_check_nccl_version(repository_ctx, nccl_install_path, nccl_hdr_path, nccl_version)
repository_ctx.template("BUILD", _NCCL_LOCAL_BUILD_TEMPLATE, {
repository_ctx.template("BUILD", _label("system.BUILD.tpl"), {
"%{version}": nccl_version,
"%{install_path}": nccl_install_path,
"%{hdr_path}": nccl_hdr_path,
})
nccl_configure = repository_rule(
implementation = _nccl_configure_impl,
environ = [
_NCCL_INSTALL_PATH,
_CUDA_TOOLKIT_PATH,
_NCCL_HDR_PATH,
_NCCL_INSTALL_PATH,
_TF_NCCL_VERSION,
_TF_CUDA_COMPUTE_CAPABILITIES,
_TF_NCCL_CONFIG_REPO,
],
)
"""Detects and configures the NCCL configuration.