Tenstorrent develops chip architecture for AI inference and learning

April 22, 2020 //By Peter Clarke
Conditional computation key to Tenstorrent AI processor
Tenstorrent Inc., (Toronto, Ontario), founded in 2016, has announced its chip architecture intended to perform both inference and learning for artificial intelligence.

The company calls it "the first conditional execution architecture for artificial intelligence" for inference and learning and has announced its flagship product: Grayskull.

The processor's architecture scales from battery-powered IoT devices to large cloud servers, Tentorrent claims and the company's team comprises alumni from hardware companies such as Nvidia and AMD. The company is backed by Real Ventures and Eclipse Venture Capital.

Tenstorrent's approach is based on the dynamic elimination of unnecessary computation – things such as multiplication by zeroes but also many other things that can be present in neural networks.

This stripping of the math load breaks the link between model size growth and computing and memory bandwidth requirements. This so-called conditional computation enables adaption of a neural network model to both exact input presented for both inference and learning. One example is natural language processing where conditional computing can dynamically prune portions of model depending on the amount of text presented and on other input characteristics.

Next: Grayskull


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