Huawei announced the official launch of the Atlas AI computing platform to the market, powered by Huawei's Ascend series AI processors.
Atlas AI offers various product form factors, such as accelerator modules, cards, AI edge stations, and appliances, providing an all-scenario AI infrastructure solution for the device-edge-cloud. It applies to fields of applications such as smart city, carriers, finance, Internet, and electric power.
Integral to Huawei's full-stack, all-scenario AI solution, the Atlas AI computing platform unlocks supreme computing power to help customers embrace an AI-fueled future. The Huawei Ascend AI processors ride on the advantages of the cutting-edge Da Vinci 3D Cube architecture, delivering ultra-high computing density and energy efficiency to enable Atlas with unrivaled AI computing power.
The Atlas series products feature the Atlas 200 AI Accelerator Module, Atlas 200 DK AI Developer Kit, Atlas 300 AI Accelerator Card, and Atlas 500 AI Edge Station.
Huawei said it will deploy a three plus one intelligent computing industry strategy based on its five types of proprietary core chips for computing, network, storage, management, and AI. Huawei aims to address the computing requirements in the device-edge-cloud scenarios by leveraging three platforms: the x86, AI, and ARM computing platforms. The three platforms are the foundation for Huawei's full-stack, all-scenario AI solutions. Meanwhile, Huawei will build an intelligent computing ecosystem around the three platforms, working with partners to lay the cornerstones for customers' digital and intelligent transformation.
Ma Haixu, Director of the Huawei Intelligent Computing Business Department
As a vital part of Huawei's AI blueprint, the Atlas AI computing platform has been applied in smart city, carrier, finance, Internet, and electric power industries. Huawei has jointly innovated with partners to launch AI-facing best practices, empowering customers with high-performance, all-scenario industry solutions to embrace pervasive intelligence.
