At the event, DeepSeek announced five of its cutting-edge software repositories, highlighted by the Fire-Flyer File System (3FS) that the company uses for AI (artificial intelligence) training and inference workloads.
Many breakthroughs in AI technology have been created by DeepSeek
Designed to optimize AI tasks, the 3FS file system has attracted attention from many experts in the field. The technology leverages the features of modern solid-state storage units and RDMA networks, creating a shared storage layer that simplifies the deployment of distributed applications. Experts at Tom's Hardware appreciate the fact that 3FS code operates without a read cache and prioritizes random read requests.
3FS is the revolution that DeepSeek brings
According to Tom's Hardware , this is important for AI models that frequently access data from servers. As a result, this distributed file system is capable of achieving aggregate read throughput of up to 6.6 TiB/sec when operating in a 180-node cluster and 3.66 TiB/min on the GraySort benchmark in a 25-node cluster.
Startup Perspective AI has also hailed these metrics as “next level,” describing 3FS as a potential revolution for data-heavy workloads related to AI and research.
What is DeepSeek and who is behind it?
In a paper published last summer, DeepSeek researchers outlined the capabilities of their custom Fire-Flyer 2 AI high-performance computing architecture. Thanks to 3FS and other elements of the software stack, DeepSeek achieved 80 percent of the performance of Nvidia’s DGX-A100 server at 50 percent of the cost and 40 percent less power.
Through Open Source Week, DeepSeek aims to emphasize transparency and community-driven innovation, and release many software products as open source repositories, including projects such as FlashMLA, DeepEP, and DeepGEMM.
Source: https://thanhnien.vn/deepseek-cong-bo-dot-pha-ve-cong-nghe-ai-185250304091501089.htm
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