Baidu, Inc. the leading Chinese language Internet search provider releases Kunlun AI chip. It is China’s first cloud-to-edge AI chip, which is built to handle AI models for both, edge computing on devices and in the cloud via data centers.
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AI applications have dramatically risen to popularity and adoption. With this, there is increased demand for requirements on the computational end. Traditional chips have limited computational power and to accelerate larger AI workloads; it requires much more scaling, computationally. To suffice this computational demand Baidu released the Kunlun AI chip, which is designed specifically for large-scale AI workloads.
Kunlun feeds the high processing demands of AI with a high-performant and cost-effective solution. It can be used for both cloud and edge instances, which include data centers, public clouds, and autonomous vehicles.
Kunlun comes in two variants; the 818-300 model is used for training and the 818-100 model is used for inference purposes. This chip leverages Baidu’s AI ecosystem including AI scenarios such as search ranking and deep learning frameworks like PaddlePaddle.
Key Specifications of Kunlun AI chip
- A computational capability which is 30 times faster than the original FPGA-based accelerator that Baidu started developing in 2011
- A 14nm Samsung engineering
- 512 GB/second memory bandwidth
- Provides 260 TOPS computing performance while consuming 100 Watts of power
The features the Kunlun chip include:
- It supports open source deep learning algorithms
- Supports a wide range of AI applications including voice recognition, search ranking, natural language processing, and so on.
Baidu plans to continue to iterate this chip and develop it progressively to enable the expansion of an open AI ecosystem. To make it successful, Baidu continues to make “chip power” to meet the needs of various fields such as intelligent vehicles and devices, voice and image recognition.
Read more about Baidu’s Kunlun AI chip on the MIT website.