forked from triton-lang/triton
-
Notifications
You must be signed in to change notification settings - Fork 7
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Windows build #3
Closed
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
* based on triton-lang#2465 * manually applied, rebased, fix lint errors * use set_target_properties(), cleanup for windows * remove '/A' platform option to use windows ninja * remove unknown option '/m' * use sysconfig.get_config_var() to get the path of python*.lib * use os.name to check dll extension * clang fix for windows * remove '-fPIC' for windows clang Original-author-by: Andrei Gheorghe <andrei@dharmaventures.co> Signed-off-by: Won-Kyu Park <wkpark@gmail.com>
* based on Windows support PR triton-lang#2456 by @andreigh * DISPATCH_ARGS fix by @andreigh * WIN32 fix using LoadLibrary
clang error "(aka 'long long') must match previous return type 'long' when lambda expression has unspecified explicit return typ"
wkpark
force-pushed
the
windows-build
branch
19 times, most recently
from
December 2, 2023 11:40
f0f5552
to
1c32e47
Compare
* use conda for ubuntu-latest * enable windows-latest build * add environment.yml * fix for windows * disable artifact check for non self-hosted * build wheels and upload dist artifacts
since the latest conda llvm+mlir 17.0.6 build does not work correctly. use the working build (built with llvm-build.yml). (use cmake/*, lib/* only)
remove clang, clangxx
wkpark
force-pushed
the
main
branch
2 times, most recently
from
December 18, 2023 08:15
aa8a948
to
04c370e
Compare
wkpark
force-pushed
the
main
branch
2 times, most recently
from
January 23, 2024 09:50
64dcce8
to
a2c9964
Compare
wkpark
force-pushed
the
main
branch
2 times, most recently
from
February 10, 2024 05:15
2507046
to
0e956cc
Compare
wkpark
pushed a commit
that referenced
this pull request
Oct 13, 2024
There are two tests that failed under AddressSanitizer: * test/TritonGPU/loop-pipeline.mlir * python/test/regression/test_functional_regressions.py with an error: ``` ==8475==ERROR: AddressSanitizer: heap-use-after-free on address 0x50c000bd0be0 at pc 0x557b03278847 bp 0x7ffd69b2c4a0 sp 0x7ffd69b2c498 READ of size 8 at 0x50c000bd0be0 thread T0 #0 0x557b03278846 in getNextOperandUsingThisValue [third_party/llvm/llvm-project/mlir/include/mlir/IR/UseDefLists.h:43](https://cs.corp.google.com/piper///depot/google3/third_party/llvm/llvm-project/mlir/include/mlir/IR/UseDefLists.h?l=43&ws=aliia/3018&snapshot=215):58 #1 0x557b03278846 in operator++ [third_party/llvm/llvm-project/mlir/include/mlir/IR/UseDefLists.h:322](https://cs.corp.google.com/piper///depot/google3/third_party/llvm/llvm-project/mlir/include/mlir/IR/UseDefLists.h?l=322&ws=aliia/3018&snapshot=215):39 #2 0x557b03278846 in mlir::ResultRange::UseIterator::operator++() [third_party/llvm/llvm-project/mlir/lib/IR/OperationSupport.cpp:614](https://cs.corp.google.com/piper///depot/google3/third_party/llvm/llvm-project/mlir/lib/IR/OperationSupport.cpp?l=614&ws=aliia/3018&snapshot=215):5 #3 0x557affde38c4 in operator++ [third_party/llvm/llvm-project/llvm/include/llvm/ADT/iterator.h:281](https://cs.corp.google.com/piper///depot/google3/third_party/llvm/llvm-project/llvm/include/llvm/ADT/iterator.h?l=281&ws=aliia/3018&snapshot=215):5 #4 0x557affde38c4 in createAsyncCopy [third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/MatmulLoopPipeline.cpp:117](https://cs.corp.google.com/piper///depot/google3/third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/MatmulLoopPipeline.cpp?l=117&ws=aliia/3018&snapshot=215):26 #5 0x557affde38c4 in createAsyncLoad [third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/MatmulLoopPipeline.cpp:135](https://cs.corp.google.com/piper///depot/google3/third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/MatmulLoopPipeline.cpp?l=135&ws=aliia/3018&snapshot=215):3 #6 0x557affde38c4 in createAsynOps [third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/MatmulLoopPipeline.cpp:501](https://cs.corp.google.com/piper///depot/google3/third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/MatmulLoopPipeline.cpp?l=501&ws=aliia/3018&snapshot=215):5 #7 0x557affde38c4 in mlir::triton::preProcessLoopAndGetSchedule(mlir::scf::ForOp&, int, mlir::triton::PipeliningOption&) [third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/MatmulLoopPipeline.cpp:740](https://cs.corp.google.com/piper///depot/google3/third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/MatmulLoopPipeline.cpp?l=740&ws=aliia/3018&snapshot=215):7 #8 0x557affe01c0c in pipelineLoop [third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/SoftwarePipeliner.cpp:76](https://cs.corp.google.com/piper///depot/google3/third_party/triton/lib/Dialect/TritonGPU/Transforms/Pipeliner/SoftwarePipeliner.cpp?l=76&ws=aliia/3018&snapshot=215):19 ... ``` This is likely happening due to iterator being invalidated after `alloc.erase()`. This PR moves erases of allocations outside of a loop and fixes heap-use-after-free issue. Do you know if there is an easy way to run the tests under sanitizers upstream? It would be handy if we can automate it, so we catch this kind of errors early on.
wkpark
pushed a commit
that referenced
this pull request
Oct 13, 2024
When running [convert_blocked1d_to_slice0](https://github.com/triton-lang/triton/blob/0ba5f0c3cd029d5c3d1f01b9bf29dac32c27345e/test/Conversion/tritongpu_to_llvm.mlir#L924) Triton ends up computing a rank of a matrix with 0 columns during linear layout lowering, which trips up f2reduce, and causes undefined behavior, detectable through [UBSAN](https://clang.llvm.org/docs/UndefinedBehaviorSanitizer.html). Fix this by returning the rank (0) early in these cases, without calling f2reduce. <details><summary>Stack trace</summary> <p> ``` third_party/triton/third_party/f2reduce/f2reduce.cpp:421:30: runtime error: shift exponent 18446744073709551615 is too large for 64-bit type 'unsigned long long' #0 0x556ee2fea3be in inplace_rref_small third_party/triton/third_party/f2reduce/f2reduce.cpp:421:30 #1 0x556ee2fea3be in f2reduce::inplace_rref_strided(unsigned long*, unsigned long, unsigned long, unsigned long) third_party/triton/third_party/f2reduce/f2reduce.cpp:470:9 #2 0x556ee2ea70da in getMatrixRank third_party/triton/lib/Tools/LinearLayout.cpp:125:3 #3 0x556ee2ea70da in mlir::triton::LinearLayout::checkInvariants(bool) third_party/triton/lib/Tools/LinearLayout.cpp:299:7 #4 0x556ee2ea656d in mlir::triton::LinearLayout::tryCreate(llvm::MapVector<mlir::StringAttr, std::__u::vector<std::__u::vector<int, std::__u::allocator<int>>, std::__u::allocator<std::__u::vector<int, std::__u::allocator<int>>>>, llvm::DenseMap<mlir::StringAttr, unsigned int, llvm::DenseMapInfo<mlir::StringAttr, void>, llvm::detail::DenseMapPair<mlir::StringAttr, unsigned int>>, llvm::SmallVector<std::__u::pair<mlir::StringAttr, std::__u::vector<std::__u::vector<int, std::__u::allocator<int>>, std::__u::allocator<std::__u::vector<int, std::__u::allocator<int>>>>>, 0u>>, llvm::ArrayRef<std::__u::pair<mlir::StringAttr, int>>, bool) third_party/triton/lib/Tools/LinearLayout.cpp:190:41 #5 0x556ee2eb2150 in mlir::triton::LinearLayout::divideRight(mlir::triton::LinearLayout const&) third_party/triton/lib/Tools/LinearLayout.cpp:654:51 #6 0x556ee2ee1c39 in mlir::cvtNeedsSharedMemory(mlir::RankedTensorType, mlir::RankedTensorType) third_party/triton/lib/Analysis/Utility.cpp:652:14 #7 0x556ee2cf38fd in mlir::triton::getRepShapeForCvtLayout(mlir::triton::gpu::ConvertLayoutOp) third_party/triton/lib/Analysis/Allocation.cpp:66:8 #8 0x556ee2cf3efa in mlir::triton::getScratchConfigForCvtLayout(mlir::triton::gpu::ConvertLayoutOp, unsigned int&, unsigned int&) third_party/triton/lib/Analysis/Allocation.cpp:95:19 #9 0x556ee2cf6057 in mlir::triton::AllocationAnalysis::getScratchValueSize(mlir::Operation*) third_party/triton/lib/Analysis/Allocation.cpp:272:24 #10 0x556ee2cf5499 in operator() third_party/triton/lib/Analysis/Allocation.cpp:343:7 #11 0x556ee2cf5499 in void llvm::function_ref<void (mlir::Operation*)>::callback_fn<mlir::triton::AllocationAnalysis::getValuesAndSizes()::'lambda'(mlir::Operation*)>(long, mlir::Operation*) third_party/llvm/llvm-project/llvm/include/llvm/ADT/STLFunctionalExtras.h:45:12 #12 0x556edeeee7a9 in operator() third_party/llvm/llvm-project/llvm/include/llvm/ADT/STLFunctionalExtras.h:68:12 #13 0x556edeeee7a9 in void mlir::detail::walk<mlir::ForwardIterator>(mlir::Operation*, llvm::function_ref<void (mlir::Operation*)>, mlir::WalkOrder) third_party/llvm/llvm-project/mlir/include/mlir/IR/Visitors.h:174:5 #14 0x556edeeee87c in void mlir::detail::walk<mlir::ForwardIterator>(mlir::Operation*, llvm::function_ref<void (mlir::Operation*)>, mlir::WalkOrder) third_party/llvm/llvm-project/mlir/include/mlir/IR/Visitors.h:182:9 #15 0x556ee2cf49e7 in walk<(mlir::WalkOrder)0, mlir::ForwardIterator, (lambda at third_party/triton/lib/Analysis/Allocation.cpp:341:42), mlir::Operation *, void> third_party/llvm/llvm-project/mlir/include/mlir/IR/Visitors.h:313:10 #16 0x556ee2cf49e7 in walk<(mlir::WalkOrder)0, mlir::ForwardIterator, (lambda at third_party/triton/lib/Analysis/Allocation.cpp:341:42), void> third_party/llvm/llvm-project/mlir/include/mlir/IR/Operation.h:794:12 #17 0x556ee2cf49e7 in mlir::triton::AllocationAnalysis::getValuesAndSizes() third_party/triton/lib/Analysis/Allocation.cpp:341:16 #18 0x556ee2cf4852 in run third_party/triton/lib/Analysis/Allocation.cpp:182:5 #19 0x556ee2cf4852 in AllocationAnalysis third_party/triton/lib/Analysis/Allocation.cpp:169:5 #20 0x556ee2cf4852 in mlir::Allocation::run(llvm::DenseMap<mlir::FunctionOpInterface, mlir::Allocation, llvm::DenseMapInfo<mlir::FunctionOpInterface, void>, llvm::detail::DenseMapPair<mlir::FunctionOpInterface, mlir::Allocation>>&) third_party/triton/lib/Analysis/Allocation.cpp:627:3 #21 0x556ee1677402 in operator() third_party/triton/include/triton/Analysis/Allocation.h:227:26 #22 0x556ee1677402 in void mlir::CallGraph<mlir::Allocation>::doWalk<(mlir::WalkOrder)0, (mlir::WalkOrder)1, mlir::ModuleAllocation::ModuleAllocation(mlir::ModuleOp)::'lambda'(mlir::CallOpInterface, mlir::FunctionOpInterface), mlir::ModuleAllocation::ModuleAllocation(mlir::ModuleOp)::'lambda'(mlir::FunctionOpInterface)>(mlir::FunctionOpInterface, llvm::DenseSet<mlir::FunctionOpInterface, llvm::DenseMapInfo<mlir::FunctionOpInterface, void>>&, mlir::ModuleAllocation::ModuleAllocation(mlir::ModuleOp)::'lambda'(mlir::CallOpInterface, mlir::FunctionOpInterface), mlir::ModuleAllocation::ModuleAllocation(mlir::ModuleOp)::'lambda'(mlir::FunctionOpInterface)) third_party/triton/include/triton/Analysis/Utility.h:350:7 triton-lang#23 0x556ee16756b3 in walk<(mlir::WalkOrder)0, (mlir::WalkOrder)1, (lambda at third_party/triton/include/triton/Analysis/Allocation.h:222:9), (lambda at third_party/triton/include/triton/Analysis/Allocation.h:224:9)> third_party/triton/include/triton/Analysis/Utility.h:242:7 triton-lang#24 0x556ee16756b3 in mlir::ModuleAllocation::ModuleAllocation(mlir::ModuleOp) third_party/triton/include/triton/Analysis/Allocation.h:220:5 triton-lang#25 0x556ee2c2bf18 in (anonymous namespace)::AllocateSharedMemory::runOnOperation() third_party/triton/lib/Conversion/TritonGPUToLLVM/AllocateSharedMemory.cpp:26:22 ... UndefinedBehaviorSanitizer: invalid-shift-exponent third_party/triton/third_party/f2reduce/f2reduce.cpp:421:30 ``` </p> </details>
wkpark
force-pushed
the
main
branch
5 times, most recently
from
October 18, 2024 03:19
3a62602
to
2cd6cce
Compare
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.