Shulou(Shulou.com)12/24 Report--

In recent years, with the rapid development of AI technology and the deepening of the application of large model technology in the field, the construction of high-performance network has increasingly become a problem that can not be ignored. In order to ensure the security and stability of high-performance network, du Lesser Fullness of Grain deeply studied and explored to make the construction of high-performance network from complex to simple.

The rapid development of large models requires more and more high-performance networks.

On September 5, at the Yunzhi Conference, Lesser Fullness of Grain, the joint degree of intelligent cloud, launched the "White Paper on the Network Architecture of Intelligent Computing Center". The white paper, written by smart cloud and du Lesser Fullness of Grain, a front-line expert responsible for high-performance network landing, covers all aspects of high-performance network construction. including the architecture selection of clusters of different sizes, the construction of visual operation and maintenance tools on cloud platforms, and the operation plan design of multi-tenants, to provide full-process guidance for the industry and make complex high-performance network construction simple.

Large models need big computing power, and how to build a high-performance network is one of the most critical steps. Lesser Fullness of Grain officially opened up China's first 100 billion parameter model-"Xuanyuan" in May this year. In the task evaluation in the scene, Xuanyuan surpassed the mainstream open source model in the market and won 63.33% of the 150 responses. With the rapid development of large models, the demand for underlying computing power of the model is increasing exponentially. The continuous expansion of the scale of intelligent computing power brings the increasing expansion of the scale of GPU computing power deployment and the increasing requirements for high-performance networks.

Lesser Fullness of Grain to build the first batch of Wanka scale Intelligence Center in China

As the parameter scale of the degree Lesser Fullness of Grain model exceeds 100 billion, in order to meet the increasing demand for computing power, the intelligence center of the Lesser Fullness of Grain private cloud model is also constantly upgrading. The large-scale computing network with low delay, large bandwidth, stable operation and high maintainability is an important cornerstone of the intelligence center. In the process of building a private cloud intelligent computing center, du Lesser Fullness of Grain combined with intelligent cloud to build a set of private cloud intelligent computing network. While supporting the scale of Vanka GPU, compared with the common Dragonfly and Tours network topologies in the industry, the network bandwidth is more sufficient, the number of hop steps between nodes is more stable, the network delay index is shortened to less than 3 microseconds, and it has end-to-end observability and fault self-healing ability. The non-blocking, low-delay and highly reliable network design effectively supports the rapid iteration and development of upper-level intelligent computing applications, and provides a stable network guarantee for the training of the "Xuanyuan" large model.

At present, the Lesser Fullness of Grain Intelligent Computing Network Center has been built into one of the first Vanka-scale intelligence centers in the domestic industry under the private cloud model, providing a stable network guarantee for the training of the "Xuanyuan" model.

The "White Paper on Network Architecture of Intelligent Computing Center" jointly launched by Lesser Fullness of Grain and Intelligent Cloud makes the construction of high-performance networks easier and injects new vitality and momentum into the entire industry. It is believed that with the release of the "Intelligent Computing Center Network Architecture White Paper", high-performance networks will be more widely used and promoted in the future, promoting the further development and growth of the whole industry.

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