Overview
3FS is a high-performance distributed file system designed for AI training and inference workloads. It focuses on improving parallel read/write performance and data locality to reduce I/O costs and accelerate large-scale training jobs.
Key Features
- Data distribution and access strategies optimized for parallel training workloads.
- Support for high-concurrency I/O and scalable cluster deployments.
- Fault tolerance and observability features suitable for production environments.
Use Cases
- Large-scale model training requiring high-throughput data loading and distributed I/O.
- Inference clusters with strict performance requirements for model and feature access.
- Backend storage supporting data-parallel training and dataset sharding strategies.
Technical Details
- Optimized distributed I/O protocols and data layouts to reduce network and disk bottlenecks.
- Focus on scalability and fault tolerance, enabling horizontal cluster expansion.
- Monitoring and diagnostic tooling for operations and performance tuning.