Merge OpenAI Triton commit 16ce143
#2807
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After this PR, `MemDesc` will be a type only in the TritonGPU dialect, as will the `TensorOrMemDesc` interface.
The pass was reordering scf.if operations without checking the extra dependencies coming from the region. For now just prevent this case although this part of the code might still be fragile.
If you build using the `CMakeLists.txt` and not `setup.py` and you build in `Release` then you get ``` /__w/triton/triton/third_party/amd/lib/TritonAMDGPUTransforms/MfmaGroup.cpp: In function ‘std::pair<mlir::Type, mlir::Type> mlir::TypesFromMfmaId(MLIRContext*, MfmaTypeId)’: Warning: /__w/triton/triton/third_party/amd/lib/TritonAMDGPUTransforms/MfmaGroup.cpp:240:1: warning: control reaches end of non-void function [-Wreturn-type] ```
While working on some higher dimension tensor kernels, I noticed poor performance due to the fact that layouts wouldn't propagate to local loads. Since we do allow layout folding with local store and local alloc, this seems like a bit of an oversight. The change gives a 40% speed improvement on certain kernels for NVidia GPUs. This also removes asserts in lowering for higher dimensional kernels. As far as I can tell, those restrictions aren't required in practice. # New contributor declaration - [x] I am not making a trivial change, such as fixing a typo in a comment. - [x] I have written a PR description following these [rules](https://cbea.ms/git-commit/#why-not-how). - [x] I have run `pre-commit run --from-ref origin/main --to-ref HEAD`. - [x] I have added tests. - [x] The `lit` tests I have added follow these [best practices](https://mlir.llvm.org/getting_started/TestingGuide/#filecheck-best-practices)
…5139) Adding a shortcut case for fp8 MFMA to dot operand layout conversion that avoids using shared memory, to speed up FP8 attention kernels.
We simplify the implementation of `getElemsPerThread` and strengthen the preconditions of `getRepForOperand`. More generally, we should try to minimise the calls to `isAmpere` and `isHopper` throughout the codebase. I'll do a pass fixing many of these once we land LLs for `ldmatrix` and Hopper.
TMA fences require CUDA toolchain 12.3 or greater, but current gating does not check the CUDA toolchain version. This causes `test_experimental_tma.py` to fail when run with older CUDA toolchains. ## Before With cuda-12.0: ``` 55 failed, 9 passed in 18.11s ``` With cuda-12.4: ``` 64 passed in 11.99s ``` ## After With cuda-12.0: ``` 9 passed, 55 skipped in 4.26s ``` With cuda-12.4: ``` 64 passed in 11.96s ```
If you build with `-DTRITON_BUILD_UT=OFF` on Mac you will get something
like
```
-- Looking for histedit.h
CMake Error at /opt/homebrew/Cellar/cmake/3.30.5/share/cmake/Modules/CheckIncludeFile.cmake:90 (try_compile):
Unknown extension ".c" for file
-- Looking for histedit.h - not found
/Users/runner/work/triton/triton/triton-build/CMakeFiles/CMakeScratch/TryCompile-QA06d6/CheckIncludeFile.c
try_compile() works only for enabled languages. Currently these are:
CXX
See project() command to enable other languages.
Call Stack (most recent call first):
llvm-bd9145c8-macos-arm64/lib/cmake/llvm/FindLibEdit.cmake:28 (check_include_file)
llvm-bd9145c8-macos-arm64/lib/cmake/llvm/LLVMConfig.cmake:177 (find_package)
llvm-bd9145c8-macos-arm64/lib/cmake/mlir/MLIRConfig.cmake:10 (find_package)
```
because `C` isn't an enabled project language.
This PR disables inline of print related functions, which speeds up compilation of test_scan_layouts dramatically. --------- Co-authored-by: Lei Zhang <[email protected]>
triton-lang/triton#5153 fixed the issue; but we missed enabling one of the disabled case.
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pbchekin
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Nov 22, 2024
whitneywhtsang
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4ae95e716ce143
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This PR change the Triton base from e9db186 to 16ce143 (Nov 22).
Pass rate: 93.24%
Please do not squash and merge this PR.