NetApp E-Series EF600 All-Flash Array

The NetApp E-Series EF600 is a high-performance all-flash storage array engineered for data-intensive computing environments requiring sustained multi-gigabyte-per-second throughput. Built on NetApp's proven E-Series architecture, the EF600 combines NVMe SSDs with a dual-controller design optimized for low-latency, high-bandwidth access patterns characteristic of GPU cluster training pipelines and scientific computing applications. The system supports both NVMe over RoCE (RDMA over Converged Ethernet) and NVMe over Fibre Channel protocols, enabling direct attachment to compute clusters without traditional SAN overhead.

The EF600 architecture emphasizes predictable performance and reliability through dedicated, non-shared storage infrastructure. Each controller features independent cache, I/O processing, and network connectivity, eliminating single points of contention. The array scales from 24 to 240+ NVMe drives in a modular expansion shelf design, supporting mixed workload profiles from sequential streaming to random-access patterns. NetApp SANtricity management software provides real-time performance telemetry, predictive analytics, and automated failover capabilities essential for research and AI environments where downtime directly impacts project timelines.

Deployed extensively across national laboratories, academic research institutions, and AI centers, the EF600 has become a standard building block for GPU-accelerated training clusters. Its tight integration with NVIDIA DGX systems and AMD MI series infrastructure, combined with native Linux kernel NVMe/RoCE drivers, enables streamlined validation and rapid deployment cycles typical of high-performance research environments.

Ideal for

• AI model training acceleration: direct-attached storage for distributed GPU clusters training large language models and deep neural networks with multi-terabyte datasets
• HPC simulation and scientific computing: sustained multi-GB/s throughput for computational fluid dynamics, molecular dynamics, and finite-element analysis workflows
• Real-time analytics on streaming data: sub-millisecond latency data pipelines for financial modeling, scientific sensor networks, and live video processing
• Genomics and bioinformatics processing: high-concurrency access patterns for variant analysis, sequencing alignment, and population-scale genetic databases
• Machine learning inference clusters: low-latency feature vector storage and model checkpoint access for production inference platforms
• Research data repository: persistent tier-1 storage for multi-institutional collaborations requiring 100%+ uptime and predictable performance

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.