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| author |  Ilya Biryukov <ibiryukov@google.com> | 2018-09-04 03:09:52 -0700 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2018-09-04 03:15:01 -0700 |
| commit | 1c3d02eb3594e9d92cd26562e797142ee34505b2 (patch) | |
| tree | 72fe9f6b489c76f4db86699f37209f57938f6eb2 /configure.py | |
| parent | d45cd10714906326ab1e27a82260a8dc56028671 (diff) | |
Use LLD when building with downloaded GPU toolchain
This improves build times when using the downloaded clang toolchain.
Additionally, remove '-B/usr/bin' flags from the cuda CROSSTOOL when using
the downloaded toolchain.
It was forcing 'clang' to first search for the linker in '/usr/bin',
preventing downloaded LLD from being selected.
PiperOrigin-RevId: 211430374
Diffstat (limited to 'configure.py')
| -rw-r--r-- | configure.py | 4 |
1 files changed, 4 insertions, 0 deletions
diff --git a/configure.py b/configure.py index 7edab53964..361bd4764d 100644 --- a/configure.py +++ b/configure.py @@ -1543,6 +1543,10 @@ def main(): if environ_cp.get('TF_DOWNLOAD_CLANG') != '1': # Set up which clang we should use as the cuda / host compiler. set_clang_cuda_compiler_path(environ_cp) + else: + # Use downloaded LLD for linking. + write_to_bazelrc('build:cuda_clang --config=download_clang_use_lld') + write_to_bazelrc('test:cuda_clang --config=download_clang_use_lld') else: # Set up which gcc nvcc should use as the host compiler # No need to set this on Windows |