Arm 推出新一代 Ethos-U NPU及全新物联网参考设计平台，加速边缘 AI

By Paul Williamson, SVP and GM of the IoT LoB, Arm

April 9, 2024 -- As edge AI scales, silicon innovators must navigate growing system and software complexity, an ever-increasing demand for AI performance and pressure to accelerate their time-to-market. At the same time, software developers need more consistent, streamlined experiences and easy integration with emerging AI frameworks and libraries.

Introducing our new third generation NPU for edge AI, the Arm Ethos-U85

Today we are announcing our highest performance, most efficient Ethos NPU to date, the Arm Ethos-U85. Delivering a 4x performance uplift and 20% higher power efficiency compared to its predecessor while scaling from 128 to 2048 MAC units (4 TOPs @1GHz), the Ethos-U85 is addressing applications where we see even greater performance demands such as factory automation and commercial or smart home cameras. Ethos-U85 offers the same consistent toolchain so partners can leverage existing investments for a seamless developer experience. Importantly, it provides support for AI frameworks such as TensorFlow Lite and PyTorch.

Ethos-U85 supports Transformer Networks as well as Convolutional Neural Networks (CNNs) for AI inference. Transformer Networks will drive new applications, particularly in vision and generative AI use cases for tasks like understanding videos, filling in missing parts of images or analyzing data from multiple cameras for image classification and object detection.

With the deployment of microprocessors into more high-performance IoT systems for use cases such as industrial machine vision, wearables and consumer robotics, we’ve designed the Ethos-U85 to work with our leading Armv9 Cortex-A CPUs, to accelerate ML tasks and bring power-efficient edge inference into a broader range of higher-performing devices.

The Ethos family of NPUs has been licensed by more than 20 partners to date, and early adopters of the new Ethos-U85 include Alif and Infineon. Read more about the Arm Ethos-U85 here.

“Machine learning workloads for the next generation of edge AI applications demand high performance in a power efficient manner,” said Reza Kazerounian, co-founder and president, Alif Semiconductor. “Alif was the first to market with an edge AI solution based on Arm Cortex-M55 and Ethos-U55, and we welcome Arm’s latest AI technology, Ethos-U85, which will deliver the compute performance required for our next generation Ensemble family of microcontrollers and fusion processors to address future edge AI and vision use cases.”

“Edge AI use cases are becoming increasingly sophisticated and require secure, high performance compute systems to deliver on the opportunities of the AI era,” said Steve Tateosian, SVP of Industrial MCUs, IoT, Wireless and Compute Business, Infineon. “We look forward to building on Infineon’s long-standing partnership with Arm and enabling these sophisticated systems with Arm Ethos-U85 and the transformer network support it provides for edge AI deployments.”

New IoT Reference Design Platform, Corstone-320, accelerates voice, audio, and vision systems

Introducing the Arm Corstone-320 IoT Reference Design Platform, bringing together our highest performance Arm Cortex-M85 CPU, our Mali-C55 Image Signal Processor and the brand-new Ethos-U85 NPU, to deliver the performance required to span the broad range of edge AI applications for voice, audio, and vision, such as real time image classification and object recognition, or enabling voice assistants with natural language translation on smart speakers. The platform includes software, tools, and support including Arm Virtual Hardware. This combination of hardware and software will accelerate product timelines by enabling software development to start ahead of silicon being available, rapidly improving time to market for these increasingly complex edge AI devices. Read more about Arm Corstone-320 here.

The IoT and embedded industry is looking to Arm to scale the edge AI opportunity

As AI adoption grows, everyone from startup innovators to the world’s biggest microcontroller players are converging on Arm as the platform of choice to deliver their AI solutions from cloud to edge.