Nvidia, ARM aim to bring AI to billions of IoT devices
Under the partnership, the companies will integrate the open-source NVIDIA Deep Learning Accelerator (NVDLA) architecture into ARM’s Project Trillium platform for machine learning. The collaboration, say the companies, will make it simple for IoT chip companies to integrate AI into their designs and help put intelligent, affordable products into the hands of billions of consumers worldwide.
“Inferencing will become a core capability of every IoT device in the future,” says Deepu Talla, vice president and general manager of Autonomous Machines at NVIDIA. “Our partnership with ARM will help drive this wave of adoption by making it easy for hundreds of chip companies to incorporate deep learning technology.”
Rene Haas, executive vice president, and president of the IP Group, at ARM adds, “Accelerating AI at the edge is critical in enabling ARM’s vision of connecting a trillion IoT devices. Today we are one step closer to that vision by incorporating NVDLA into the Arm Project Trillium platform, as our entire ecosystem will immediately benefit from the expertise and capabilities our two companies bring in AI and IoT.”
NVDLA is a free, open architecture designed to promote a standard way to design deep learning inference accelerators. Based on the Nvidia Xavier autonomous machine SoC, its modular architecture is scalable, highly configurable and designed to simplify integration and portability.
NVDLA is supported by NVIDIA’s suite of developer tools, including upcoming versions of TensorRT, a programmable deep learning accelerator. The open-source design, says the company, allows for cutting-edge features to be added regularly, including contributions from the research community.
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