IBM AIU: an AI ASIC that does more than ‘separate cats from dogs’ in photos

A SoC with 32 processing units and 23 billion transistors available as a PCIe card.

IBM Research introduces its SoC AIU (Artificial Intelligence Unit). According to the company, it is an ASIC (application-specific integrated circuit) “designed to run and train deep learning models faster and more efficiently than a CPU”. This solution takes the form of a PCIe card.

Jeffrey Burns and Leland Chang, the authors of the publication, specify that the SoC has 32 processing cores and 23 billion transistors. This quantity is roughly equivalent to that of the z16, an “AI and cyber-resilience” platform based on IBM’s Telum processor. In fact, Jeffrey Burns and Leland Chang explain that the AIU SoC was not built from scratch, but rather is “a scaled-up version of an already proven artificial intelligence accelerator, integrated to our Telum chip”. Thus, “IBM’s AIU’s 32 cores are very similar to the AI ​​cores built into the Telum chip”. However, Telum uses transistors fabricated on a 7nm process, while those of the AIU benefit from 5nm etching.

IBM unveils the first wafer engraved in 2 nm

Improve AI hardware efficiency by a factor of 2.5 every year

These are the only technical details shared by IBM for now. However, the company aims to contribute to the rapid development of AI; not to detect dogs or cats in photos, as we can read in the article, but rather to face the great challenges of the coming years. This mission falls to researchers at the AI ​​Hardware Center, which was founded in 2019.

Here are the terms used by Jeffrey Burns and Leland Chang:

“The AI ​​cores embedded in Telum, and now our first dedicated AI chip, are the product of the AI ​​Hardware Center’s aggressive roadmap to increase IBM’s hardware firepower. ‘IA. Due to the time and expense involved in training and running deep learning models, we have barely scratched the surface of what AI can offer, especially for businesses.

We inaugurated the AI ​​Hardware Center in 2019 to fill this void, with a mission to improve AI hardware efficiency by 2.5 times every year. By 2029, our goal is to train and run AI models a thousand times faster than three years ago.

Deploying AI to distinguish cats from dogs in photos is a fun academic exercise. But that won’t solve the pressing problems we face. For AI to tackle real-world complexities — things like predicting the next Hurricane Ian, or knowing if we’re heading into a recession — we need professional-grade, industrial-scale hardware. . Our IAU brings us closer. We hope to be able to inform you of its release soon.”

Source : IBM Research

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IBM AIU: an AI ASIC that does more than ‘separate cats from dogs’ in photos


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