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Intel oneDNN 3.6 Improves Performance For Granite Rapids, Initial Xe2 Optimizations

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  • Intel oneDNN 3.6 Improves Performance For Granite Rapids, Initial Xe2 Optimizations

    Phoronix: Intel oneDNN 3.6 Improves Performance For Granite Rapids, Initial Xe2 Optimizations

    Intel engineers have released the oneAPI Deep Neural Network Library "oneDNN" version 3.6 release that serves as the building blocks for deep learning software like ONNX Runtime, OpenVINO, Apache MXNet, Apache SIGNA, and optionally by PyTorch and TensorFlow with Intel's extensions...

    Phoronix, Linux Hardware Reviews, Linux hardware benchmarks, Linux server benchmarks, Linux benchmarking, Desktop Linux, Linux performance, Open Source graphics, Linux How To, Ubuntu benchmarks, Ubuntu hardware, Phoronix Test Suite

  • #2
    Originally posted by phoronix View Post
    Phoronix: Intel oneDNN 3.6 Improves Performance For Granite Rapids, Initial Xe2 Optimizations

    Intel engineers have released the oneAPI Deep Neural Network Library "oneDNN" version 3.6 release that serves as the building blocks for deep learning software like ONNX Runtime, OpenVINO, Apache MXNet, Apache SIGNA, and optionally by PyTorch and TensorFlow with Intel's extensions...

    https://www.phoronix.com/news/Intel-oneDNN-3.6
    Exciting news! Intel oneDNN 3.6 is now available! Immediate Xe2 enhancements and Granite Rapids speed boosts bode well for deep learning applications. By making frameworks like PyTorch and ONNX Runtime more efficient, this update could open up new options for developers. I am eagerly looking forward to witnessing the practical implications of this!

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    • #3
      Originally posted by watsicagaylord View Post

      Exciting news! Intel oneDNN 3.6 is now available! Immediate Xe2 enhancements and Granite Rapids speed boosts bode well for deep learning applications. By making frameworks like PyTorch and ONNX Runtime more efficient, this update could open up new options for developers. I am eagerly looking forward to witnessing the practical implications of this!
      This could be an essential step toward making Intel hardware more competitive in AI and machine learning tasks, especially as deep learning continues to demand more powerful processing capabilities.

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