ASUS RS720A-E11-RS12U 2U AMD EPYC 12-Bay GPU Server

The ASUS RS720A-E11-RS12U is a 2U rack-optimised server platform built on the AMD EPYC 7003 and 9004 series processor architecture, delivering high core counts, expansive memory bandwidth, and PCIe 4.0 connectivity across a compact dual-socket capable chassis. Designed to meet the demands of GPU-accelerated computing, the system accommodates up to 12 large-form-factor drives alongside multiple full-height, full-length GPU or accelerator cards, making it a highly versatile platform for dense AI inference, model training, and HPC deployments within 2U of rack space.

The RS720A-E11-RS12U supports substantial DDR4 registered ECC memory across its DIMM slots, providing the memory capacity and bandwidth required to feed multiple concurrent GPU workloads without becoming a bottleneck. Its PCIe Gen 4 fabric enables high-throughput communication between the host processor and attached accelerators, while dual 10GbE or optional higher-speed networking options facilitate low-latency data ingestion from storage and upstream compute tiers. ASUS ASMB10-iKVM out-of-band management integration gives datacenter operators remote monitoring, power control, and system health visibility without requiring physical access to the node.

Targeted at enterprise datacenters, cloud service providers, and research institutions across the UAE, GCC, EMEA, and APAC regions, the RS720A-E11-RS12U is positioned as a high-density, operationally mature GPU server capable of supporting demanding AI, deep learning, scientific simulation, and virtualised GPU workloads. Its 2U form factor enables organisations to maximise accelerator density per rack unit while retaining the thermal headroom and redundant power infrastructure expected of production-grade enterprise hardware.

Ideal for

• Large-scale AI model training using multi-GPU configurations with frameworks such as TensorFlow and PyTorch on AMD EPYC-powered compute nodes
• Enterprise inference serving for natural language processing, computer vision, and recommendation system models requiring high-throughput GPU acceleration
• High-performance computing (HPC) simulations in engineering, life sciences, and financial modelling that benefit from dense parallel processing within a 2U footprint
• GPU-accelerated virtual desktop infrastructure (VDI) deployments serving concurrent enterprise users requiring dedicated graphics resources
• Distributed deep learning research clusters where multiple RS720A-E11-RS12U nodes are interconnected to form scalable training fabric in colocation or on-premises datacenters
• Data analytics and scientific computing pipelines that combine high local NVMe or SAS/SATA storage capacity with GPU acceleration for in-situ data processing

Technical specifications

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