Huawei unveils Atlas artificial intelligence hardware

Huawei has released its Atlas computing platform, which is powered by its new Ascend series of artificial intelligence chips.

It announced the new devices during Huawei Connect 2018, its annual conference in Shanghai.

“The Atlas intelligent computing platform integrates various forms of products, such as modules, cards, boards, edge stations, and appliances, to build an all-scenario AI infrastructure covering the end, edge, and cloud,” Huawei said.

Huawei also said that the new Atlas platform is an evolution of the cloud hardware platform it released last year, and consists of several devices.

These include the Atlas 200 AI accelerator module aimed at terminals, the Atlas 300 AI accelerator card designed for data centre use, the Atlas 500 AI edge station, and the Atlas 800 AI appliance, positioned for enterprises.

The key features of Huawei’s new Atlas product line are summarised below:

  • Atlas 200 AI acceleration module: Half the size of a credit card, supports 16-channel real-time HD video analytics, consumes about 10W of power, deployed on devices such as cameras and drones.
  • Atlas 300 AI acceleration card: Half-height and half-length PCIe standard card form factor, aimed at data centre and edge server scenarios.
  • Atlas 600 accelerator card: Supports multiple data precisions, and delivers up to 64 trillion operations per second (TeraOPS) with 8-bit integers.
  • Atlas 500 AI edge station: Size of a set-top box (DStv decoder), offers AI processing capabilities, supports 16-channel HD video processing with 4× performance increase over existing products.
  • Atlas 800 AI appliance: Ready to go within 2 hours after being unboxed through using a standard framework and programming environment for AI, integrated software for cluster management and job scheduling, and system-level performance monitoring.

Now read: Huawei Ascend 910 AI chip unveiled – the greatest computing density on a single chip

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Huawei unveils Atlas artificial intelligence hardware