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AI Storage Network

Storage That Keeps Pace with AI:
Ultra-Low Latency, Lossless RoCE, Elevated +10% IOPS
Ultra-Fast, Congestion-Free, Ready for AI

AI Storage Network

Highest-performance AI Ethernet fabric
Better than InfiniBand
  
  
  

Ultra-Low Latency Lossless RoCE Network accelerates storage protocols such as NVMeoF, Ceph, and distributed file systems like Lustre or HDFS, by reducing read/write latency and boosting IOPS. Delivers 5–10% performance improvement compared to InfiniBand.

Ultra-low-latency

Network

Lossless RoCE

Network

↑ 5~10%

IOPS Beyond IB

The Value of AI Storage Network

Infographic of AI storage network topology showcasing Storage Frontend Network and Backend Network architecture, with key metrics on IOPS improvement, latency reduction, lossless transport, and congestion-free routing.

AI Storage Network Topology

Click to enlarge
  • Improve IOPS 
    Read performance increased by 3-6%, and write performance increased by 6-10%.
  • Reduce I/O Latency 
    Read latency is reduced by 3–6%, and write latency decreases by up to 10%.
  • Lossless Transport 
    RoCEv2 with PFC, ECN, and DCBX ensures zero packet loss, delivering high throughput for storage traffic.
  • Congestion Free 
    INT-driven Adaptive Routing measures real-time link utilization and dynamically bypasses congested paths to minimize tail latency for storage workloads.

Traffic

RoCE + DiffServ enables the convergence of diverse storage traffic on a single physical network — including model and dataset loading, RAG vector database access, logging, and input/output backup. It supports protocols such as NVMe-oF, Ceph, BeeGFS, Lustre, S3, NFS, and HDFS, ensuring lossless delivery for critical flows while maintaining high throughput across the system.

Protocol
RDMA Support
Latency Sensitivity
Throughput Demand
Typical Use Case
NVMe-oF
Yes
High
High
Fast block storage for AI/ML
training/inference
Ceph
Optional
Medium
High
Distributed object storage for
large datasets
BeeGFS
Optional
Medium
High
HPC parallel file system for
performance
Lustre
Yes
High
High
HPC and AI parallel I/O
workloads
S3
No
Low
Medium
Cloud-native object storage
(e.g., backups)
NFS
No
Low
Medium
General purpose
file access
HDFS
No
Low
High
Big Data processing
(e.g., Hadoop)

Test Result

Using the ultra-low-latency CX-532P-N RoCE switch, two compute nodes and two NVMe-oF storage nodes were interconnected via ConnectX-5 adapters. Storage performance was evaluated with vdbench 5.04.06 and fio 2.1.10 (4KB/8KB random workloads), and results were compared against a Mellanox SB7700 InfiniBand switch.

AI Storage Network Read and Write Latency between Asterfusion CX-N and Mellanox SB7700 switches

In single compute–storage node latency tests, the RoCE switch reduced read latency by up to 6.3% and write latency by up to 10.1% compared with the InfiniBand switch.

AI Storage Network Read and Write IOPS performance between Asterfusion CX-N and Mellanox SB7700 switches under dual-server workloads

In multi-flow concurrent IOPS tests between two compute nodes and two storage nodes, read IOPS improved by up to 6.1% and write IOPS improved by up to 10.5%.

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