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Accelerated Linear Algebra
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<h2 id="supported-target-devices">Supported target devices</h2> <ul><li><a href="/facts/X86-64/cyWvUFlP">x86-64</a></li> <li><a href="/facts/ARM64/bauXRos7">ARM64</a></li> <li><a href="/facts/NVIDIA/8QfCgqbu">NVIDIA</a> GPU</li> <li><a href="/facts/AMD/CB1G7QTb">AMD</a> GPU</li> <li><a href="/facts/Intel/SMF0gJJX">Intel</a> GPU<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a></li> <li><a href="/facts/Apple_Inc./oTJYta3k">Apple</a> GPU<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a></li> <li><a href="/facts/Google/GT9Sugza">Google</a> <a href="/facts/Tensor_Processing_Unit/aVlg0LFF">TPU</a></li> <li><a href="/facts/Amazon_Web_Services/UFVN2796">AWS</a> Trainium, Inferentia<a class="footnote-ref" id="fnref:7" href="#fn:7"><sup>7</sup></a></li> <li><a href="/facts/Cerebras/Xu4HUfJl">Cerebras</a><a class="footnote-ref" id="fnref:8" href="#fn:8"><sup>8</sup></a></li> <li><a href="/facts/Graphcore/Yb9IMBWt">Graphcore</a> IPU<a class="footnote-ref" id="fnref:9" href="#fn:9"><sup>9</sup></a></li></ul> <h2 id="see-also">See also</h2> <ul><li><a href="/facts/TensorFlow/kDwfBeNd">TensorFlow</a></li> <li><a href="/facts/PyTorch/4Gv1t13B">PyTorch</a><a class="footnote-ref" id="fnref:10" href="#fn:10"><sup>10</sup></a></li> <li><a href="/facts/Google_JAX/MnxmwXqc">JAX</a></li></ul> <h2 id="references">References</h2> <ol> <li id="fn:1"><p>"OpenXLA Project". Retrieved December 21, 2024. <a href="https://openxla.org/" target="_blank">https://openxla.org/</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li> <li id="fn:2"><p>Woodie, Alex (2023-03-09). "OpenXLA Delivers Flexibility for ML Apps". Datanami. Retrieved 2023-12-10. <a href="https://www.datanami.com/2023/03/08/openxla-delivers-flexibility-for-ml-apps/" target="_blank">https://www.datanami.com/2023/03/08/openxla-delivers-flexibility-for-ml-apps/</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li> <li id="fn:3"><p>"TensorFlow XLA: Accelerated Linear Algebra". TensorFlow Official Documentation. Retrieved 2023-12-10. <a href="https://www.tensorflow.org/xla" target="_blank">https://www.tensorflow.org/xla</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li> <li id="fn:4"><p>Smith, John (2022-07-15). "Optimizing TensorFlow Models with XLA". Journal of Machine Learning Research. 23: 45–60. <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li> <li id="fn:5"><p>"intel/intel-extension-for-openxla". GitHub. Retrieved December 29, 2024. <a href="https://github.com/intel/intel-extension-for-openxla/" target="_blank">https://github.com/intel/intel-extension-for-openxla/</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li> <li id="fn:6"><p>"Accelerated JAX on Mac - Metal - Apple Developer". Retrieved December 29, 2024. <a href="https://developer.apple.com/metal/jax/" target="_blank">https://developer.apple.com/metal/jax/</a> <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li> <li id="fn:7"><p>"Developer Guide for Training with PyTorch NeuronX — AWS Neuron Documentation". awsdocs-neuron.readthedocs-hosted.com. Retrieved 29 December 2024. <a href="https://awsdocs-neuron.readthedocs-hosted.com/en/latest/frameworks/torch/torch-neuronx/programming-guide/training/pytorch-neuron-programming-guide.html" target="_blank">https://awsdocs-neuron.readthedocs-hosted.com/en/latest/frameworks/torch/torch-neuronx/programming-guide/training/pytorch-neuron-programming-guide.html</a> <a href="#fnref:7" class="footnote-back-ref">↩</a></p></li> <li id="fn:8"><p>Barsoum, Emad (13 April 2022). "Supporting PyTorch on the Cerebras Wafer-Scale Engine - Cerebras". Cerebras. Retrieved 29 December 2024. <a href="https://cerebras.ai/blog/supporting-pytorch-on-the-cerebras-wafer-scale-engine/" target="_blank">https://cerebras.ai/blog/supporting-pytorch-on-the-cerebras-wafer-scale-engine/</a> <a href="#fnref:8" class="footnote-back-ref">↩</a></p></li> <li id="fn:9"><p>Ltd, Graphcore. "Poplar® Software". graphcore.ai. Retrieved 29 December 2024. <a href="https://www.graphcore.ai/products/poplar" target="_blank">https://www.graphcore.ai/products/poplar</a> <a href="#fnref:9" class="footnote-back-ref">↩</a></p></li> <li id="fn:10"><p>"PyTorch/XLA documentation — PyTorch/XLA master documentation". pytorch.org. Retrieved 29 December 2024. <a href="https://pytorch.org/xla/" target="_blank">https://pytorch.org/xla/</a> <a href="#fnref:10" class="footnote-back-ref">↩</a></p></li> </ol>