End AI Storage Bottlenecks with NFS over RDMA | QNAP
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End AI Storage Bottlenecks
with NFS over RDMA
Any I/O latency (in milliseconds) wastes the computational power of expensive GPUs. The combination of the TS-h1290FX and NFS over RDMA ensures that storage performance keeps pace with computational speed.
[1] Learn NFS over RDMA
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 US$24 per hour. If GPU utilization drops to 60% while waiting for data, approximately US$10 per hour is completely wasted.
Why NFS over RDMA Changes Everything
By leveraging Kernel Bypass and Zero-Copy technologies, we eliminate the redundant memory copies and CPU overhead inherent in traditional NFS. All protocol processing is offloaded to the hardware, drastically minimizing the time your GPUs spend waiting for data.
100x Latency Reduction
Real-time response for AI training.
85% CPU Load Reduction
Free up your servers for actual computing.
Near Line-Rate Throughput
Achieve up to 100Gbps speed across the network.
<5% GPU Wait Time
Keep your expensive GPUs working at full capacity.
Stop Settling for Legacy Storage Bottlenecks
Feature
QNAP TS-h1290FX
Standard SATA NAS
Performance
NFS over RDMA (Native)
Unsupported (Legacy TCP)
Latency
Ultra-Low (Microseconds)
High (Milliseconds)
CPU Usage
Minimized via RDMA
Heavy Overhead
Drive Interface
U.2 NVMe PCIe Gen 4
SATA 6Gb/s
Ready to Accelerate Your Enterprise AI?
Upgrade to the TS-h1290FX All-Flash Array and unleash the full potential of your compute nodes.
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References:
1. https://qnap.benchurl.com/c/l?u=13E016DD&e=1B5E6C5&c=47C09&t=0&seq=1
2. https://qnap.benchurl.com/c/l?u=13E016DE&e=1B5E6C5&c=47C09&t=0&seq=1
3. mailto:marketing@qnap.com
4. https://qnap.benchurl.com/c/l?u=13E016DF&e=1B5E6C5&c=47C09&t=0&seq=1
5. https://qnap.benchurl.com/c/l?u=13E016E0&e=1B5E6C5&c=47C09&t=0&seq=1
6. https://qnap.benchurl.com/c/l?u=13E016E1&e=1B5E6C5&c=47C09&t=0&seq=1
7. https://qnap.benchurl.com/c/l?u=13E016E2&e=1B5E6C5&c=47C09&t=0&seq=1
8. https://qnap.benchurl.com/c/l?u=13E016E3&e=1B5E6C5&c=47C09&t=0&seq=1