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    <title>PyTorch — USASI news</title>
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    <description>Dated, sourced news items in the USASI catalog that mention PyTorch. Independent project. Not a United States government website.</description>
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    <lastBuildDate>Tue, 20 Oct 2026 12:00:00 GMT</lastBuildDate>
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      <title>Amazon announces an Apache 2.0 release of TorchNeuron, a native PyTorch backend for AWS Trainium</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/amazon-open-sources-torchneuron-for-trainium/</link>
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      <pubDate>Tue, 20 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>Amazon said TorchNeuron, which it describes as running existing PyTorch code on its Trainium chips without a rewrite by plugging into PyTorch's standard mechanism for registering new hardware, would be released under the Apache 2.0 license at PyTorch Conference North America on October 20, 2026. Amazon says TorchNeuron supports Trainium2 and Trainium3 and that it is contributing changes upstream to PyTorch. The aws-neuron/torch-neuronx repository on GitHub is public, lists the Apache License 2.0, and describes itself as a native PyTorch backend for AWS Trainium. A Hugging Face blog post dated October 19 describes running Hugging Face models with it. USASI has not tested TorchNeuron.</description>
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    <item>
      <title>PyTorch 2.14.0 released with torch.switch, NVGEMM in Inductor, and a preview NCCL backend rewrite</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/pytorch-2-14-0-released/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>PyTorch 2.14.0 was published on GitHub on September 2, 2026. The release notes highlight NVGEMM, which brings CuTeDSL-generated CUTLASS kernels to Inductor, and torch.switch, which generalizes torch.cond to multi-way branching. Other highlights include declarative dynamic shapes via @dynamic_spec, experimental torch.compile support for complex-valued tensors, a preview of a rewritten NCCL backend ported from torchcomms, and native linear algebra on Apple Silicon. The notes also say Inductor now targets Rubin (sm_107). USASI has not tested this release.</description>
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    <item>
      <title>PyTorch 2.13.0 released with FlexAttention on Apple Silicon and the torchcomms backend</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/pytorch-2-13-0-released/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>PyTorch 2.13.0 was published on GitHub on July 8, 2026. The release notes highlight FlexAttention support on Apple Silicon (MPS) and a deterministic FlexAttention backward path on CUDA, a prototype CuTeDSL &quot;Native DSL&quot; backend for Inductor alongside Triton, and nn.LinearCrossEntropyLoss, which combines the final prediction and loss computation to reduce peak GPU memory. They also introduce torchcomms, a new communications backend for PyTorch Distributed, and Python 3.15 wheels on Linux, while dropping free-threaded CPython 3.13t binaries and Bazel build support. USASI has not tested this release.</description>
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