Improve Fused8BitRowwiseQuantizedSBFloatToFloatOrHalfNeon by 5%-15% #8948
Triggered via pull request
March 21, 2025 15:07
Status
Failure
Total duration
1h 53m 14s
Artifacts
40
fbgemm_gpu_ci_cuda.yml
on: pull_request
Matrix: build_artifact
Matrix: test_and_publish_artifact
Annotations
3 errors
test_and_publish_artifact (x86, linux.g5.4xlarge.nvidia.gpu, 3.12, 11.8.0, 12.4.1, clang)
Process completed with exit code 1.
|
test_and_publish_artifact (x86, linux.g5.4xlarge.nvidia.gpu, 3.10, 12.8.0, 12.4.1, clang)
Process completed with exit code 1.
|
test_and_publish_artifact (x86, linux.g5.4xlarge.nvidia.gpu, 3.10, 12.4.1, 12.4.1, clang)
Process completed with exit code 1.
|
Artifacts
Produced during runtime
Name | Size | Digest | |
---|---|---|---|
fbgemm_gpu_nightly_cuda_x86_clang_py3.10_cu11.8.0.whl
|
263 MB |
sha256:1677a1dd469a2176ca5ea293a0531f5c54b79e26a6fabd39a9fbf3e06b1cc42b
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.10_cu12.4.1.whl
|
509 MB |
sha256:577f374f376393a47d87c20952ed113182bf9e5aafe2358ded452e5d46eb730d
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.10_cu12.6.3.whl
|
507 MB |
sha256:004f285ae435198c58e240185ad3758a8e218c5550fba991c963d42cb9873fcc
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.10_cu12.8.0.whl
|
967 MB |
sha256:5934837e2ca885b470173bdf563544491350d9b872f9a86c5878856d3008f3d7
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.11_cu11.8.0.whl
|
263 MB |
sha256:b1b065912be87e1196b5dc1c4f654362a65bd692e9e5d539c818efd3191c1802
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.11_cu12.4.1.whl
|
509 MB |
sha256:01b3732cb5c498ef7b0edd4b2b808e98dbd429611fd2feae257bdcbcc9870ef2
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.11_cu12.6.3.whl
|
507 MB |
sha256:96857f22c5d1335902b3bbbcf66bf4ae32e12aecdde2983c8da1e9d55a64708d
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.11_cu12.8.0.whl
|
967 MB |
sha256:7c3ec996b2a90c6de0c81a469639a69004c8380c13fe3c2a21cc88413bd74cc9
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.12_cu11.8.0.whl
|
263 MB |
sha256:0ef49dd5e9004067d713cc38be3af27402de92e17f3ed546901b45f968d12399
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.12_cu12.4.1.whl
|
509 MB |
sha256:29d6281e8fdd227722770e7347a451a6a5e525c2b23f2f242c462696dc76bc72
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.12_cu12.6.3.whl
|
507 MB |
sha256:c7c5bff16c07dcde0d0ac227a80654abaa1df6b411acd2a78a82d72d47866f64
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.12_cu12.8.0.whl
|
967 MB |
sha256:839996f2fdafadf6593240f9213a71f921a7d12f38e453c1ed969bda7bcdac8f
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.13_cu11.8.0.whl
|
263 MB |
sha256:cc96f9a81fba1110a93b795f4c2c86b61ac85b2773e6f6e6e607827adb80fd31
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.13_cu12.4.1.whl
|
509 MB |
sha256:9ad3e7691d7cfdac61f19780554dd3855f99d1b6b801de875fa00ad65d20cb45
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.13_cu12.6.3.whl
|
507 MB |
sha256:f307c4c3b59d9488ef63e237b36119c991c6707f03cf5971102142b8ea4118c7
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.13_cu12.8.0.whl
|
967 MB |
sha256:4265a52c46f4d8ba58e7c7991262197b1059a7c51d10c4cd72c08d58b9ceece6
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.9_cu11.8.0.whl
|
263 MB |
sha256:4a2a2df46222e19424bcada0aa88409327818b87e79fb757ae2ca9ab00f64243
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.9_cu12.4.1.whl
|
509 MB |
sha256:5e8b35b463be3e530019e39ec681ece8905a9b202a73a8afc10f86690e1208f5
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.9_cu12.6.3.whl
|
507 MB |
sha256:c700b157906c3332d82f22ba5b88aa9aae3535f9b4180bcaf782331d34d001fa
|
|
fbgemm_gpu_nightly_cuda_x86_clang_py3.9_cu12.8.0.whl
|
967 MB |
sha256:84a36af5d3cb2b03fa66c32e71bd4aa36cc602c6f593d87e3a16bb4c287a631a
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.10_cu11.8.0.whl
|
261 MB |
sha256:bcd54b81f2d9f591059246c51d3948cdeda0d916cdb751970deacf6c2bc3c22f
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.10_cu12.4.1.whl
|
507 MB |
sha256:33e3f72a8c3af3d86c0bbde94b5cc4acbe0b82944babea772a4ed17028e5df8c
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.10_cu12.6.3.whl
|
504 MB |
sha256:a28fd88c822da9917d570fb77831eff98dd7829c5e692f7099cf33c604c59efd
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.10_cu12.8.0.whl
|
962 MB |
sha256:a2143221ac1bce6ed08a02357c520efd90122bbd3666b8b677d6e9fa03769396
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.11_cu11.8.0.whl
|
261 MB |
sha256:3208df658c56d71cb55fdda472793cf6fa29554c6dab7dcff5484bc59f9a51ad
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.11_cu12.4.1.whl
|
507 MB |
sha256:d9b87a704addb9197465b2d198520713c595e33e644de30cd6c0a727d11dbc9f
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.11_cu12.6.3.whl
|
504 MB |
sha256:b265e9aad2be1801ac38d8d06ec955870f7d94d95c303ad60ce4cde308cf8682
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.11_cu12.8.0.whl
|
962 MB |
sha256:840ef115fc38349a53fa3cf6ff2d3ef3ac33d5416d2cb08d9ea2da6dc4b4ff39
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.12_cu11.8.0.whl
|
261 MB |
sha256:8d3c1357ba70d03014265e82572429cadeaf0c51c0b3a8bf2c12146afc48afde
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.12_cu12.4.1.whl
|
507 MB |
sha256:4bd0ab8a10aad62a825a46524615f3429ee0aa8705abe200bdd59584661dbbc5
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.12_cu12.6.3.whl
|
504 MB |
sha256:4375e32fa54bf6c8b4c69a14041724ede718c6c8c390675992fac216c605fbb2
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.12_cu12.8.0.whl
|
962 MB |
sha256:22b3fb5721a323fc98b8a2739ab9b9a4f90dc632968168255f5bda506f38203c
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.13_cu11.8.0.whl
|
261 MB |
sha256:9afeff0d76227eb5d252f80be7a880aeda05fd0a9c4e51cb1913d28cef347e58
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.13_cu12.4.1.whl
|
507 MB |
sha256:0f74f43b929ef2c5d0a19c306aae943d8e9d368ef8e92334af7c230c43b7b27b
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.13_cu12.6.3.whl
|
504 MB |
sha256:e43588cb698bc726c5ccc311cf8cdbb4c27d6847d56fa5f254d565bb18d49b71
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.13_cu12.8.0.whl
|
962 MB |
sha256:72530e644e4ca84ec69f3d11fc405d6075dc7b206a8a11faafeb7df33fa380e9
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.9_cu11.8.0.whl
|
261 MB |
sha256:c6a75204529455d836cc275ca4f7be0c86d408dd441db29d5bfe5e2b39636890
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.9_cu12.4.1.whl
|
507 MB |
sha256:8a4b5980a36e18faae25d221662ebcf358b2324a2bbf5e8bb74f47e04471e4c6
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.9_cu12.6.3.whl
|
504 MB |
sha256:ced5c8a18def23620147718a2b3542f0b624275582d9847593def1ff01c1174b
|
|
fbgemm_gpu_nightly_cuda_x86_gcc_py3.9_cu12.8.0.whl
|
962 MB |
sha256:da046c7f9a011553b34cac108f22267c7148791d86258b3af21cf137a3589c97
|
|