Supermicro AS-4124GS-TNR2 AMD EPYC GPU Server

The Supermicro AS-4124GS-TNR2 is a 4U AMD EPYC-based GPU server engineered for high-density artificial intelligence, machine learning, and HPC workloads. Built on the AMD EPYC 7003 series (Milan) processor platform, the system supports dual AMD EPYC processors delivering high core counts, large memory bandwidth, and PCIe 4.0 connectivity — providing the computational backbone required to feed multiple high-performance GPUs simultaneously. The chassis accommodates up to 8 double-width GPU accelerators, making it well suited for large-scale deep learning training and parallel compute tasks that demand both raw throughput and memory capacity.

The AS-4124GS-TNR2 features an expansive DDR4 memory subsystem supporting up to 4TB of registered ECC memory across 32 DIMM slots, ensuring data integrity for mission-critical enterprise workloads. Storage flexibility is addressed through multiple NVMe and SATA/SAS drive bays, enabling fast local scratch storage for AI datasets and model checkpointing. Dual 10GbE and additional high-speed networking interfaces facilitate rapid data ingestion and cluster interconnects, while redundant 3000W platinum-level power supplies maintain continuous operation under full GPU load.

Designed for deployment in enterprise datacenters and GPU compute clusters across financial services, healthcare, scientific research, and large-scale cloud infrastructure, the AS-4124GS-TNR2 adheres to Supermicro's Building Block Solutions philosophy. Its tool-less GPU installation, hot-swap drive bays, and IPMI-based out-of-band management via Supermicro's BMC reduce operational overhead at scale. The platform is validated for use with leading GPU accelerators including NVIDIA A100 and H100 series cards, and supports major AI frameworks such as TensorFlow, PyTorch, and RAPIDS.

Ideal for

• Large-scale deep learning model training using multi-GPU parallelism for natural language processing and computer vision applications
• High-performance inference serving for enterprise AI platforms requiring low latency and high throughput across concurrent requests
• Scientific and engineering simulation workloads including computational fluid dynamics, molecular dynamics, and climate modeling
• Financial services quantitative analytics and real-time risk modeling leveraging GPU-accelerated compute
• Medical imaging and genomics analysis pipelines requiring high memory bandwidth and parallel data processing
• GPU cluster node deployment for cloud service providers and hyperscale datacenter operators running multi-tenant AI infrastructure

Technical specifications

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