Supermicro AS-2124GS-TNR2 2U AMD EPYC GPU Server

The Supermicro AS-2124GS-TNR2 is a 2U rackmount server engineered around AMD EPYC processors and designed to deliver high-density GPU compute for demanding enterprise AI, HPC, and data analytics environments. The platform supports dual AMD EPYC 7003 series (Milan) processors, providing a high core count architecture with PCIe 4.0 connectivity that dramatically increases bandwidth between CPUs and the installed GPU accelerators. With support for up to 4TB of DDR4 registered ECC memory across 32 DIMM slots, the system is built to handle memory-intensive inference and training workloads without bottlenecking GPU throughput.

The AS-2124GS-TNR2 accommodates up to ten NVIDIA double-wide GPU accelerators, making it one of the most GPU-dense 2U platforms in the Supermicro portfolio. The chassis features an optimized airflow design with high-performance redundant fans and tool-free GPU installation trays, enabling operational agility in production datacenter environments. High-efficiency redundant power supply units rated at 3000W provide the necessary headroom to sustain full GPU utilization across all installed accelerators simultaneously.

Networking is addressed through dual 10GbE onboard ports supplemented by dedicated IPMI management via a dedicated BMC controller, enabling out-of-band management through Supermicro's IPMI 2.0-compliant interface. The system supports NVMe storage via M.2 slots and U.2 drive bays, allowing fast local storage tiers to complement GPU memory bandwidth for checkpoint storage and dataset staging. The AS-2124GS-TNR2 is purpose-built for organizations deploying large-scale deep learning training, GPU-accelerated inference, computational fluid dynamics, seismic processing, and other throughput-sensitive workloads in modern datacenter infrastructure.

Ideal for

• Large-scale deep learning model training using frameworks such as TensorFlow and PyTorch, leveraging up to ten GPU accelerators within a single 2U chassis
• High-throughput AI inference serving for real-time enterprise applications including natural language processing, image classification, and recommendation engines
• High-performance computing workloads such as computational fluid dynamics, structural analysis, and molecular dynamics simulations requiring dense floating-point throughput
• Data analytics acceleration for large dataset processing pipelines where GPU-accelerated query engines and in-memory analytics significantly reduce time-to-insight
• Digital twin and simulation environments in manufacturing, energy, and aerospace sectors that require sustained multi-GPU parallel processing capacity
• Datacenter consolidation projects aiming to maximize GPU compute density per rack unit while maintaining enterprise-grade redundancy and remote management capabilities

Technical specifications

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