Which Trainium chips does TorchNeuron support?

Amazon has launched TorchNeuron, a tool that lets developers run their existing PyTorch code on its Trainium AI chips without rewriting it, the company said Monday. The software goes into public beta on October 20 at the PyTorch Conference in San Jose. It will be open source under the Apache 2.0 license and supports Trainium2 and Trainium3 chips.

Does TorchNeuron require rewriting PyTorch code?

Moving AI code to a new chip has long been a slow and expensive job. Until now, it often meant months of rewriting and testing. With TorchNeuron, developers point their code at Trainium by changing a single device setting, Amazon said.

In a demo, Amazon ran the same training script on a standard chip and on Trainium. The company said the model learned at the same rate on both. TorchNeuron plugs into PyTorch's built-in system for adding new hardware, so standard testing and scaling tools still work.

What PyTorch features does TorchNeuron not support yet?

The first release has gaps, though. It does not yet support some PyTorch features, such as dynamic input shapes. About 22,000 PyTorch tests are skipped, according to a PyTorch blog post written by Amazon engineers.

Early users include voice AI startups Cartesia and Deepgram, along with the Lieber Institute for Brain Development, which uses the tool in drug research. Hugging Face has also added Trainium support to its AI tools. Uber recently signed up to use the chips as part of an AWS expansion deal.

Amazon's push against Nvidia

The launch is part of Amazon's effort to compete with Nvidia, whose chips and CUDA software dominate AI computing. In April, chief executive Andy Jassy said Amazon's custom chip business could be worth $50 billion. Amazon now says the business has passed a $25 billion annual revenue run rate.

One of TorchNeuron's launch partners is Decart, an AI chip software startup that Amazon was reported to be in talks to buy.

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