)]}'
{
  "commit": "e918678414c8f4b65aeaaa810fae6adcf480509e",
  "tree": "dee8cf7b1c56dc3d2b5f4e9c38fc88c7e6a896cf",
  "parents": [
    "87a1cc6dfd25aaac5580a4e5e45d72b6c4bfd91a"
  ],
  "author": {
    "name": "Han-Chung Wang",
    "email": "hanhan0912@gmail.com",
    "time": "Tue Oct 17 17:09:46 2023 -0700"
  },
  "committer": {
    "name": "GitHub",
    "email": "noreply@github.com",
    "time": "Tue Oct 17 17:09:46 2023 -0700"
  },
  "message": "[LLVMGPU] Splitting TensorCoreVectorization to two passes. (#15184)\n\nIt delecates the vectorization step to GenericVectorization pass;\r\nrenames the pass to LLVMGPUTensorCorePreparation.\r\n\r\nIt also swaps shared memory distribution stage with\r\nTensorCorePreparation. Because the generic vectorization converts all\r\nlinalg ops to vector ops, while we apply specific logics to shared\r\nmemory distribution. We now handle special cases, vectorize\r\nlinalg.matmul; prepare the form for tensor core.",
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