fix more conflits
Resolve merge conflicts
Some more build and conflict fixes
Resolve conflicts for 06-fused-attension.py
resolve merge conflicts for the tutorial group gemm example
Fixes for some LIT tests
resolve remaining conflicts in tests
Fix empty kernel
set capability 0
This is a combination of 4 commits.
Works as StandAlone and Backend
Works as StandAlone and Backend
This is a combination of 13 commits.
Works StandAlone and as Backend
This is a combination of 7 commits.
backend set default dir with flag
move bitcode to backend dir
copy backend
save
empty test work in backendmode
enable backend mode when copying to upstream
clean up
fix failure
minimize diff
add skip function
fix bug with corrupted dwarf exp
match num_wraps
fix multi threaded test issue
move bitcode file out of lib
move backend to python/triton/third_party/hip
move libhsa
backend works again
restart ci
clean upstream location first before copy
match scripts
fix new error
memoize backend stuff
fix bug
* this pr adds a third party backend for triton that works on AMD
* this expose a lot of the work that has been done in our
[fork](https://github.com/ROCmSoftwarePlatform/triton)
* most unit tests on `test_core.py` pass
* it skips some unit tests for various reasons
* we plan to follow up with more prs improving Functionality and
Performance in the future
---------
Co-authored-by: Philippe Tillet <phil@openai.com>
By default, ptxas will enable fusion of mul/add to fma instructions. The
backend was also being configured unconditionally to enable this on
conversion from LLVM IR to PTX. This commit adds an option which can be
used to disable the FP fusion behavior in both locations.
* Restructure ROCM Library Search
Currently there are a handful of ROCM dependant files which are required for
triton to run. The linker(ld.lld), the include files, and multiple hip/hsa
shared objects.
This change will provide three search areas to find these files. All in
the same order.
1. third_party/rocm. This location is within the python/triton directory
and is carried over when triton is built. IF all necessary files
are in this location there will be no need to have ROCM installed at
all on the system.
2. $ROCM_PATH environmental variable. If this exists it will override
all other locations to find ROCM necessary files
3. /opt/rocm. The default location for ROCm installations. Finding one
here will notify triton that ROCM is installed in this environment
To ease with step 3. A new script scripts/amd/setup_rocm_libs.sh
has been added to the repo. Executing this script will cause all necessary
ROCM files to be downloaded from their respective packages on repo.radeon.com
and installed in third_party/rocm. Allowing for triton to run without installing
the full ROCM stack. setup_rocm_libs.sh takes a env_var ROCM_VERSION if a user
wishes to install a ROCM version other than the default (currently 5.4.2)
When triton whls are built to support Pytorch, method 3 will be used to stay in
sync with PyTorch's approach of bringing along any libraries needed and not
requiring ROCM to be installed.
(cherry picked from commit e6aea90fb3e8218cb562e5d990719112d8282702)
* Fix default rocm path
Running into `fatal error: hip/hip_runtime.h: No such file or directory` with latest wheel due to incorrect directory for ROCm libs
(cherry picked from commit 292bae625b113eb65c66cfe4442da7a6456c988a)
* setup_rocm_libs.sh manylinux refactor
(cherry picked from commit f995f314ada4606cb78dc6233cd9c8effc356191)
* Set setup_rocm_libs.sh to be executable
(cherry picked from commit 05d67b9418cacda0d356c2102d7c1a887948b013)
* Revert to using numbered so files to fix upstream
(cherry picked from commit 34f8189eae57a23cc15b4b4f032fe25757e0db8e)
* Remove drm script
---------
Co-authored-by: Jeff Daily <jeff.daily@amd.com>
We've seen cases where the entire kernel is poisoned due to
division-by-zero, resulting in a single `unreachable` instruction at the
LLIR level. Emit this instruction as `trap` (instead of dropping it) so
that the kernel doesn't run successfully without writing any outputs.
Add infrastructure to be able to add and test custom LLVM passes in the
backend. This will allow use to apply some low level optimizations and
cleanup on LLVM IR.
Add a first pass that breaks up phi of struct created by lowering to
LLVM. Those can often pessimise the optimizer as it would block
optimizations going through phi nodes.
.. instead of an option.
This partially addresses https://github.com/openai/triton/issues/2265 to
no longer crash when printing a pass pipeline in textual form.
It is not a proper solution for the fact that pass results should be
stored in the IR and not in a pointer argument.
* this pr adds a third party backend for triton that works on AMD
* this expose a lot of the work that has been done in our
[fork](https://github.com/ROCmSoftwarePlatform/triton)
* most unit tests on `test_core.py` pass
* it skips some unit tests for various reasons
* we plan to follow up with more prs improving Functionality and
Performance in the future
---------
Co-authored-by: Philippe Tillet <phil@openai.com>
Before this PR, the determination of `TritonGPUToLLVMIRPass` to generate
NVVM-compatible LLVM or ROCDL-compatible LLVM is controlled by a boolean
`isROCM`. This method is hard to scale.
This PR changes it to use an enum instead, where new target can be added
easily when needed.
---------
Signed-off-by: Tsang, Whitney <whitney.tsang@intel.com>
Co-authored-by: Philippe Tillet <phil@openai.com>
For example, when given `--convert-triton-gpu-to-llvm="is-rocm=true"`,
`ConvertTritonGPUToLLVMPass` should generate ROCM-compatible LLVM.
Before this PR, transformation options passed in command line are not
respected.
No functional changes intended, and it might slightly speed up the
build.
This allows a downstream Bazel build of Triton to avoid building a
number of dialects and passes that Triton doesn't need.
The initial code merge of Nvidia Hopper features support. Please be
aware that the code merge is not finished yet and the trouble-shooting
is still ongoing. The new hardware features (GMMA, TMA, STMATRIX etc.)
and automatic warp-specialization are experimental for now and turned
off by default. It is recommended for a trial when version 3.0 is
released.
The work is contributed by:
ben-zhang-609, bealwang, donproc, qliu93, jsh20, allatit23, LyricZhao,
ivanyinwz, goostavz & yangjunpro
from Nvidia, in cooperation with:
ptillet, Jokeren, ThomasRaoux & zahimoud
from OpenAI.
Co-authored-by: Goostav Zhu <gzhu@nvidia.com>
That library makes use of the dladdr function, so it eventually needs to
be linked with -ldl, which may not be done automatically. This commit
adds a link dependency to `${CMAKE_DL_LIBS}`, which is CMake's way of
specifying that library in a portable way.
Also try to switch APIs access to the new upstream APIs that separate
explicitly the access to "discardable" and "inherent" attributes (the
latter being stored in properties now).
Generic accessors like `getAttr()` `setAttr()` `setAttrs()` are much
more expensive and to be avoided.
Conflicts:
lib/Conversion/TritonGPUToLLVM/TritonGPUToLLVMPass.cpp
lib/Target/LLVMIR/LLVMIRTranslation.cpp
python/test/unit/language/assert_helper.py
python/triton/third_party/cuda/bin/ptxas
test/Conversion/tritongpu_to_llvm.mlir
It looks like you may be committing a merge.
If this is not correct, please remove the file
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and try again.
This is a combination of 7 commits.
use pyt nightly with root
repro with pytorch unit test
hardcode isROCM to true
set is_cuda to False
ignore cc arg
clean up
match triton-mlir branch
