Day 5 of Open-Source Week: DeepSeek AI Unveils 3FS & Smallpond

DeepSeek AI has announced Fire-Flyer File System (3FS), a high-speed distributed file system, and Smallpond, a lightweight data processing framework. Together, they significantly enhance AI training, inference, and large-scale data management by leveraging modern SSDs and RDMA networks for record-breaking performance.

Why 3FS Matters

AI models require enormous amounts of data for training, testing, and real-time inference. Traditional storage systems often become bottlenecks, slowing down development. 3FS eliminates these limitations by offering:

• Extreme Speed: Achieves 6.6 TiB/s aggregate read throughput in a 180-node cluster.

• Scalability: Uses a disaggregated architecture, meaning storage is separated from compute resources, improving efficiency.

• AI Optimization: Handles training data preprocessing, dataset loading, checkpoint saving, and KVCache lookups for inference—critical tasks for AI development.

Key Performance Highlights

• 3.66 TiB/min throughput on the GraySort benchmark, proving its ability to process massive datasets rapidly.

• 40+ GiB/s peak throughput per client for KVCache lookups, an essential function for optimizing large language models (LLMs).

• Efficient Data Processing: Integrated with Smallpond, a new data framework that enhances large-scale dataset handling.

What Smallpond Does

• High-performance data processing powered by DuckDB.

• Scalable for petabyte-scale datasets.

• Easy to use, with no need for long-running services.

Why Smallpond Matters

Smallpond works alongside 3FS to accelerate sorting, querying, and analyzing massive datasets, making it valuable for AI research, big data analytics, and cloud-based storage solutions. It was benchmarked using the GraySort test, where it processed 110.5 TiB of data in just 30 minutes—a major achievement in speed and efficiency.

Looking Ahead

DeepSeek AI’s 3FS and Smallpond could set a new standard for AI storage and data processing, particularly for organizations dealing with large-scale machine learning and big data analytics. These innovations have the potential to speed up AI research, reduce costs, and improve efficiency worldwide.

🔗 Learn More & Access 3FS and Smallpond:

3FS: GitHub Repository

Smallpond: GitHub Repository

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.