In the model inference scenario, DeepSeek introduces large model API caching technology, which caches the first calculated token data to the hard disk and uses cache hits to optimize subsequent output and save computing resources. However, traditional storage architecture still faces the following challenges:

Local storage limitations: The PCIe channel of the local computing server is insufficient, which limits the mounting scale of the local SSD hard disk, resulting in limited cache capacity, inability to fully utilize the read and write speed, and affecting model inference efficiency.

File system performance bottleneck: When using a file system to mount large-capacity storage, file system performance issues in the remote storage cluster (such as metadata management, data consistency maintenance, network latency, etc.) will reduce storage performance, limit the potential of hard disk caching technology, cause data reading speed to slow down, and affect the efficiency of inference task execution.

Reasoning delay problem: In complex task scenarios, the above problems will cause excessive reasoning delay and affect the user experience. Especially in scenarios that require real-time response such as financial transaction analysis and autonomous driving, it may lead to delayed decision-making and miss key business opportunities.

In response to these problems, LUISUAN Technology's all-flash storage and Light Boat series products break through local storage limitations and file system bottlenecks, becoming the key to improving storage performance. This optimization can not only significantly improve the performance of DeepSeek's large model API caching technology, but also reduce computing power costs and improve return on investment (ROI). The optimized system can handle complex reasoning tasks more efficiently, reduce delays, improve user experience, and bring significant advantages to enterprises in market competition.

In the context of digital transformation, it is crucial to build an efficient and reliable hard disk cache system. Continuous optimization of storage architecture and file system performance will help enterprises cope with future challenges and achieve sustainable development.