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Amazon Web Services 发布了 TorchNeuron 开发工具，让 PyTorch 应用仅需一行配置即可迁移到其 Trainium AI 芯片上，直接挑战 Nvidia 在 AI 软件生态上的主导地位，并将相关改动贡献给 PyTorch 上游项目。
Amazon 发布 TorchNeuron，让现有 PyTorch 代码无需重写即可原生运行在 AWS Trainium 芯片上，并将于 10 月 20 日 PyTorch Conference 上开源。该工具旨在降低开发者切换 AI 硬件的成本，已有多家企业在机器人、自动驾驶、大模型等领域采用。
PyTorch and AWS announce TorchNeuron, an open-source native PyTorch backend for AWS Trainium chips, letting developers run existing PyTorch code with a simple `.to('neuron')` switch, supporting eager execution, torch.compile, and NKI custom kernels. It will launch as public beta under Apache 2.0 at the PyTorch Conference on Oct. 20.
TorchNeuron 作为 PyTorch 的原生 Trainium 后端发布公测，Hugging Face 的 Transformers、Diffusers 等库可直接将其作为普通设备使用，显著提升了模型支持率并取代 Optimum Neuron 的复杂封装。
AWS 宣布 PyTorch 现已原生支持 AWS Trainium 芯片，并将在 PyTorch Conference North America（10月20-21日，圣何塞）由 Amazon VP Distinguished Engineer Robert Hundt 发表主题演讲、AWS Neuron Principal PM Maen Suleiman 进行现场演示。
PyTorch Conference North America 宣布 AWS 副总裁兼杰出工程师 Robert Hundt 将担任主题演讲嘉宾，分享 Trainium 如何获得原生 PyTorch 支持，涵盖 eager mode、torch.compile、TorchTitan 与 TorchAO。会议将于 10 月 20-21 日在圣何塞举行。
PyTorch Conference North America will feature a session by AWS's Esha Lakhotia and Pinak Panigrahi on profiling PyTorch workloads on AWS Trainium, covering torch.profiler capture through cycle-level hardware debugging with AI-assisted analysis. The event takes place in San Jose on October 20-21.
At PyTorch Conference North America, Colin Brace will present on AWS Trainium's native integration with PyTorch, detailing technical advancements and ecosystem contributions.
AccelOpt is a self-improving LLM agentic system that autonomously optimizes AI accelerator kernels through iterative generation and optimization memory, achieving 49-61% peak throughput improvements on AWS Trainium while being 26x cheaper than Claude Sonnet 4.