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Add 2.8 release notes worksheet for Intel GPU (XPU). #12
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Hi @etaf! Thank you for your pull request. We require contributors to sign our Contributor License Agreement, and yours needs attention. You currently have a record in our system, but the CLA is no longer valid, and will need to be resubmitted. ProcessIn order for us to review and merge your suggested changes, please sign at https://code.facebook.com/cla. If you are contributing on behalf of someone else (eg your employer), the individual CLA may not be sufficient and your employer may need to sign the corporate CLA. Once the CLA is signed, our tooling will perform checks and validations. Afterwards, the pull request will be tagged with If you have received this in error or have any questions, please contact us at [email protected]. Thanks! |
2.8.0/done/result_xpu.md
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- Support int4 WOQ GEMM on Intel GPU ([#137566](https://github.com/pytorch/pytorch/pull/137566)) | ||
- Support third_party SYCL kernels with CPP Extension API ([#132945](https://github.com/pytorch/pytorch/pull/132945)) | ||
- Support safe softmax for SDPA on Intel GPU ([#151999](https://github.com/pytorch/pytorch/pull/151999)) | ||
- SupportGQA and different head_dim of value for SDPA on Intel GPU([#150992](https://github.com/pytorch/pytorch/pull/150992)) |
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It should be an improvement rather than a new feature.
2.8.0/done/result_xpu.md
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- Support Intel distributed backend (XCCL) in PyTorch ([#141856](https://github.com/pytorch/pytorch/pull/141856)) | ||
- Support int4 WOQ GEMM on Intel GPU ([#137566](https://github.com/pytorch/pytorch/pull/137566)) | ||
- Support third_party SYCL kernels with CPP Extension API ([#132945](https://github.com/pytorch/pytorch/pull/132945)) | ||
- Support safe softmax for SDPA on Intel GPU ([#151999](https://github.com/pytorch/pytorch/pull/151999)) |
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It should be an improvement rather than a new feature.
2.8.0/done/result_xpu.md
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- Improve scalar tensor case handling in addmm, baddmm on Intel GPU ([#153051](https://github.com/pytorch/pytorch/pull/153051)) | ||
- Support f32 intermediate dtype, headdim <= 576, and f32 causal mask for SDPA ([#152091](https://github.com/pytorch/pytorch/pull/152091)) | ||
- Add Intel GPU device support for nested_layer_norm ([#148593](https://github.com/pytorch/pytorch/pull/148593)) | ||
- Refine oneDNN context manager API on Intel GPU ([#147349](https://github.com/pytorch/pytorch/pull/147349)) |
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Let's remove it.
2.8.0/done/result_xpu.md
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### bug fixes | ||
- Fix matmul accuracy when offset > 0 ([#154495](https://github.com/pytorch/pytorch/pull/154495)) | ||
- Correct torch.xpu.is_bf16_supported to return False if no Intel GPU detected ([#152317](https://github.com/pytorch/pytorch/pull/152317)) |
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- Correct torch.xpu.is_bf16_supported to return False if no Intel GPU detected ([#152317](https://github.com/pytorch/pytorch/pull/152317)) | |
- Fix the issue that `torch.xpu.is_bf16_supported` always returns `True` even if Intel GPU is not available ([#152317](https://github.com/pytorch/pytorch/pull/152317)) |
2.8.0/done/result_xpu.md
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- Add Intel GPU device support for nested_layer_norm ([#148593](https://github.com/pytorch/pytorch/pull/148593)) | ||
- Refine oneDNN context manager API on Intel GPU ([#147349](https://github.com/pytorch/pytorch/pull/147349)) | ||
- Improve error handling and reporting in Intel GPU CMake files ([#149353](https://github.com/pytorch/pytorch/pull/149353)) | ||
- Support multi_arch_kernel_binary option in AOTInductor for Intel GPU ([#154514](https://github.com/pytorch/pytorch/pull/154514)) |
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Pls. consolidate AOTI-related improvements into a single bullet.
2.8.0/done/result_xpu.md
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- Support Intel GPU profiler toggle functionality ([#155135](https://github.com/pytorch/pytorch/pull/155135)) | ||
- Support distributed memory tracker integration for Intel GPU ([#150703](https://github.com/pytorch/pytorch/pull/150703)) | ||
- Improve scalar tensor case handling in addmm, baddmm on Intel GPU ([#153051](https://github.com/pytorch/pytorch/pull/153051)) | ||
- Support f32 intermediate dtype, headdim <= 576, and f32 causal mask for SDPA ([#152091](https://github.com/pytorch/pytorch/pull/152091)) |
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Pls. consolidate SDPA-related improvement into a single bullet.
Co-authored-by: Eikan Wang <[email protected]>
Co-authored-by: Eikan Wang <[email protected]>
Co-authored-by: Eikan Wang <[email protected]>
Co-authored-by: Eikan Wang <[email protected]>
2.8.0/done/result_xpu.md
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- Add memory reporting to Memory Profiler for Intel GPU ([#152842](https://github.com/pytorch/pytorch/pull/152842)) | ||
- Support Intel GPU profiler toggle functionality ([#155135](https://github.com/pytorch/pytorch/pull/155135)) | ||
- Support distributed memory tracker integration for Intel GPU ([#150703](https://github.com/pytorch/pytorch/pull/150703)) | ||
- Improve scalar tensor case handling in addmm, baddmm on Intel GPU ([#153051](https://github.com/pytorch/pytorch/pull/153051)) |
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Let's move this bullet to performance
section. Because it reduces the oneDNN integration overhead.
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Only one minor comments and looks good.
2.8.0/done/result_xpu.md
Outdated
- Add Intel GPU device support for nested_layer_norm ([#148593](https://github.com/pytorch/pytorch/pull/148593)) | ||
- Refine oneDNN context manager API on Intel GPU ([#147349](https://github.com/pytorch/pytorch/pull/147349)) | ||
- Improve error handling and reporting in Intel GPU CMake files ([#149353](https://github.com/pytorch/pytorch/pull/149353)) | ||
- Support multi_arch_kernel_binary option in AOTInductor for Intel GPU ([#154514](https://github.com/pytorch/pytorch/pull/154514)) |
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if code, use single quotes 'multi_arch_kernel_binary'
@jbschlosser please help to comment and merge it. Thanks. |
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