PyTorch大会发布面向Google TPU和AWS Trainium的原生后端
据PyTorch Blog报道，PyTorch Conference North America 2026于10月20日至21日在圣何塞举行，吸引了3500多名参会者，议题覆盖开放智能、研究、模型、基础设施、硬件和生产。大会推出开源项目TorchTPU，这是Google与Meta的合作成果，为Google TPU提供原生PyTorch后端；并启动采用Apache 2.0许可证的TorchNeuron公开测试版，该项目为AWS Trainium提供原生后端。其他更新涉及IBM Spyre编译器开发和面向AMD MI350系列GPU的可选后端。TorchTitan还扩大了其5D并行技术栈支持的模型范围，并通过TitanRL加入强化学习能力。
大会为Google TPU和AWS Trainium增加了原生PyTorch后端，为研究人员和从业者提供了两种新的PyTorch工作负载硬件选择。IBM Spyre和AMD项目属于编译器及后端开发，并非同等性质的原生后端发布。
PyTorch Conference North America 2026 brought 3,500+ attendees to San Jose on October 20–21 for two days focused on accelerating open intelligence and exploring the impact of PyTorch Foundation projects like PyTorch, vLLM, DeepSpeed, Ray, Helion, and Safetensors.
PyTorch Foundation Executive Director, Mark Collier, set the stage for the entire event to demonstrate how the PyTorch Foundation is building the open source software to train and serve models on any chip, in any cloud, for any agent.
Accelerating Open Intelligence Together
Mark Collier’s opening keynotes connected work across research, models, frameworks, infrastructure, hardware, and production. Day 1 examined how shared advances across those layers help the community move faster together. Day 2 looked ahead to broader hardware participation, workloads moving across more environments, and training and customizing frontier models at greater scale.
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