Storage Data Path#
conceptstub
What it is#
The path that feeds data and models to GPUs and absorbs checkpoints: object storage, parallel file systems (Lustre, Weka, GPFS), local NVMe caches, and GPUDirect Storage.
Why it matters#
GPUs that wait for data are wasted. Training reads large datasets continuously and writes multi-terabyte checkpoints in bursts; inference loads large model weights at startup. Storage runs in parallel with the network data path, so it is designed alongside the fabric, not after it.
In this module#
A data path parallel to L6–L9: feeding GPUs and absorbing checkpoints.
Planned content
- Data path: object storage → parallel FS → local NVMe → GPU
- CSI drivers: local NVMe, Rook/Ceph, Lustre, Weka
- Checkpoint bursts and spot/preemptible recovery
- GPUDirect Storage