Your GPU might be wasting time waiting for data
While the cost of AI training is determined by GPU runtime, storage I/O bottlenecks could be wasting more than 40% of your computation time.
1. The Hidden Cost of the TCP Stack
Every time data is read, the CPU is occupied with processing TCP packets and context switching. Although this contributes nothing to AI computations, it secretly consumes up to 99% of CPU resources.
2. 4–6 rounds of wasted memory copies
With traditional NFS, data is copied between the kernel and user space 4–6 times before reaching the GPU, and every 1 microsecond of added latency results in lost computational power.
3. Real-world losses from GPU idle time
For example, in an 8×H100 cluster, cloud costs exceed $24 per hour. If GPU utilization drops to 60% while waiting for data, approximately $10 per hour is completely wasted.
