forked from OSchip/llvm-project
3a1c81e327
A simple sed doing these substitutions:
- `${LLVM_BINARY_DIR}/lib${LLVM_LIBDIR_SUFFIX}\>` -> `${LLVM_LIBRARY_DIR}`
- `${LLVM_BINARY_DIR}/bin\>` -> `${LLVM_TOOLS_BINARY_DIR}`
where `\>` means "word boundary".
The only manual modifications were reverting changes in
- `runtimes/CMakeLists.txt`
because these were "entry points" where we wanted to tread carefully not not introduce a "loop" which would end with an undefined variable being expanded to nothing.
There are some `${LLVM_BINARY_DIR}/lib` without the `${LLVM_LIBDIR_SUFFIX}`, but these refer to the lib subdirectory of the source (`llvm/lib`). That `lib` is automatically appended to make the local `CMAKE_CURRENT_BINARY_DIR` value by `add_subdirectory`; since the directory name in the source tree is fixed without any suffix, the corresponding `CMAKE_CURRENT_BINARY_DIR` will also be. We therefore do not replace it but leave it as-is.
This picks up where D133828 left off, getting the occurrences with*out* `CMAKE_CFG_INTDIR`. But this is difficult to do correctly and so not done in the (retroactively) previous diff.
This hopefully increases readability overall, and also decreases the usages of `LLVM_LIBDIR_SUFFIX`, preparing us for D130586.
Reviewed By: sebastian-ne
Differential Revision: https://reviews.llvm.org/D132316
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| .. | ||
| cmake | ||
| docs | ||
| include/polly | ||
| lib | ||
| test | ||
| tools | ||
| unittests | ||
| utils | ||
| www | ||
| .arclint | ||
| .gitattributes | ||
| .gitignore | ||
| CMakeLists.txt | ||
| CREDITS.txt | ||
| LICENSE.TXT | ||
| README | ||
README
Polly - Polyhedral optimizations for LLVM ----------------------------------------- http://polly.llvm.org/ Polly uses a mathematical representation, the polyhedral model, to represent and transform loops and other control flow structures. Using an abstract representation it is possible to reason about transformations in a more general way and to use highly optimized linear programming libraries to figure out the optimal loop structure. These transformations can be used to do constant propagation through arrays, remove dead loop iterations, optimize loops for cache locality, optimize arrays, apply advanced automatic parallelization, drive vectorization, or they can be used to do software pipelining.