ABataev added a comment. In D99432#2726997 <https://reviews.llvm.org/D99432#2726997>, @estewart08 wrote:
> In D99432#2726845 <https://reviews.llvm.org/D99432#2726845>, @ABataev wrote: > >> In D99432#2726588 <https://reviews.llvm.org/D99432#2726588>, @estewart08 >> wrote: >> >>> In D99432#2726391 <https://reviews.llvm.org/D99432#2726391>, @ABataev wrote: >>> >>>> In D99432#2726337 <https://reviews.llvm.org/D99432#2726337>, @estewart08 >>>> wrote: >>>> >>>>> In D99432#2726060 <https://reviews.llvm.org/D99432#2726060>, @ABataev >>>>> wrote: >>>>> >>>>>> In D99432#2726050 <https://reviews.llvm.org/D99432#2726050>, @estewart08 >>>>>> wrote: >>>>>> >>>>>>> In D99432#2726025 <https://reviews.llvm.org/D99432#2726025>, @ABataev >>>>>>> wrote: >>>>>>> >>>>>>>> In D99432#2726019 <https://reviews.llvm.org/D99432#2726019>, >>>>>>>> @estewart08 wrote: >>>>>>>> >>>>>>>>> In reference to https://bugs.llvm.org/show_bug.cgi?id=48851, I do not >>>>>>>>> see how this helps SPMD mode with team privatization of declarations >>>>>>>>> in-between target teams and parallel regions. >>>>>>>> >>>>>>>> DiŠ² you try the reproducer with the applied patch? >>>>>>> >>>>>>> Yes, I still saw the test fail, although it was not with latest >>>>>>> llvm-project. Are you saying the reproducer passes for you? >>>>>> >>>>>> I don't have CUDA installed but from what I see in the LLVM IR it shall >>>>>> pass. Do you have a debug log, does it crashes or produces incorrect >>>>>> results? >>>>> >>>>> This is on an AMDGPU but I assume the behavior would be similar for NVPTX. >>>>> >>>>> It produces incorrect/incomplete results in the dist[0] index after a >>>>> manual reduction and in turn the final global gpu_results array is >>>>> incorrect. >>>>> When thread 0 does a reduction into dist[0] it has no knowledge of >>>>> dist[1] having been updated by thread 1. Which tells me the array is >>>>> still thread private. >>>>> Adding some printfs, looking at one teams' output: >>>>> >>>>> SPMD >>>>> >>>>> Thread 0: dist[0]: 1 >>>>> Thread 0: dist[1]: 0 // This should be 1 >>>>> After reduction into dist[0]: 1 // This should be 2 >>>>> gpu_results = [1,1] // [2,2] expected >>>>> >>>>> Generic Mode: >>>>> >>>>> Thread 0: dist[0]: 1 >>>>> Thread 0: dist[1]: 1 >>>>> After reduction into dist[0]: 2 >>>>> gpu_results = [2,2] >>>> >>>> Hmm, I would expect a crash if the array was allocated in the local >>>> memory. Could you try to add some more printfs (with data and addresses of >>>> the array) to check the results? Maybe there is a data race somewhere in >>>> the code? >>> >>> As a reminder, each thread updates a unique index in the dist array and >>> each team updates a unique index in gpu_results. >>> >>> SPMD - shows each thread has a unique address for dist array >>> >>> Team 0 Thread 1: dist[0]: 0, 0x7f92e24a8bf8 >>> Team 0 Thread 1: dist[1]: 1, 0x7f92e24a8bfc >>> >>> Team 0 Thread 0: dist[0]: 1, 0x7f92e24a8bf0 >>> Team 0 Thread 0: dist[1]: 0, 0x7f92e24a8bf4 >>> >>> Team 0 Thread 0: After reduction into dist[0]: 1 >>> Team 0 Thread 0: gpu_results address: 0x7f92a5000000 >>> -------------------------------------------------- >>> Team 1 Thread 1: dist[0]: 0, 0x7f92f9ec5188 >>> Team 1 Thread 1: dist[1]: 1, 0x7f92f9ec518c >>> >>> Team 1 Thread 0: dist[0]: 1, 0x7f92f9ec5180 >>> Team 1 Thread 0: dist[1]: 0, 0x7f92f9ec5184 >>> >>> Team 1 Thread 0: After reduction into dist[0]: 1 >>> Team 1 Thread 0: gpu_results address: 0x7f92a5000000 >>> >>> gpu_results[0]: 1 >>> gpu_results[1]: 1 >>> >>> Generic - shows each team shares dist array address amongst threads >>> >>> Team 0 Thread 1: dist[0]: 1, 0x7fac01938880 >>> Team 0 Thread 1: dist[1]: 1, 0x7fac01938884 >>> >>> Team 0 Thread 0: dist[0]: 1, 0x7fac01938880 >>> Team 0 Thread 0: dist[1]: 1, 0x7fac01938884 >>> >>> Team 0 Thread 0: After reduction into dist[0]: 2 >>> Team 0 Thread 0: gpu_results address: 0x7fabc5000000 >>> -------------------------------------------------- >>> Team 1 Thread 1: dist[0]: 1, 0x7fac19354e10 >>> Team 1 Thread 1: dist[1]: 1, 0x7fac19354e14 >>> >>> Team 1 Thread 0: dist[0]: 1, 0x7fac19354e10 >>> Team 1 Thread 0: dist[1]: 1, 0x7fac19354e14 >>> >>> Team 1 Thread 0: After reduction into dist[0]: 2 >>> Team 1 Thread 0: gpu_results address: 0x7fabc5000000 >> >> Could you check if it works with `-fno-openmp-cuda-parallel-target-regions` >> option? > > Unfortunately that crashes: > llvm-project/llvm/lib/IR/Instructions.cpp:495: void > llvm::CallInst::init(llvm::FunctionType*, llvm::Value*, > llvm::ArrayRef<llvm::Value*>, > llvm::ArrayRef<llvm::OperandBundleDefT<llvm::Value*> >, const llvm::Twine&): > Assertion `(i >= FTy->getNumParams() || FTy->getParamType(i) == > Args[i]->getType()) && "Calling a function with a bad signature!"' failed. Hmm, could you provide a full stack trace? Repository: rG LLVM Github Monorepo CHANGES SINCE LAST ACTION https://reviews.llvm.org/D99432/new/ https://reviews.llvm.org/D99432 _______________________________________________ cfe-commits mailing list cfe-commits@lists.llvm.org https://lists.llvm.org/cgi-bin/mailman/listinfo/cfe-commits
