SGLang Brings AWS Trainium Support via TorchNeuron
SGLang now runs on a second major accelerator family beyond NVIDIA GPUs, lowering the barrier for teams wanting cheaper inference and RL infrastructure on AWS. Developers running open model serving can sign up for the beta and evaluate Trainium as an alternative to GPU instances. Singapore and ASEAN teams using AWS's growing regional data-centre footprint can test it without waiting for general availability.
The SGLang team announced beta support for AWS Trainium accelerators. The integration is built on TorchNeuron, AWS's native PyTorch backend, so SGLang's model components and abstractions carried over largely intact. The team also reported its first end-to-end heterogeneous reinforcement learning run on the platform. Beta sign-up is available through the announcement blog.
Welcome AWS Trainium to the SGLang family!
Built on TorchNeuron, AWS’s native PyTorch backend, so SGLang’s model components and abstractions carried over largely intact. Our write-up covers what’s in the beta, why we built on TorchNeuron from day one, and our first end-to-end heterogeneous RL run. Beta sign-up is in the blog!
https://t.co/Lhbb9IkXMq
