Supermicro GPU System GS-A21GPU4T 4U Multi-GPU Storage Optimized

The Supermicro GS-A21GPU4T is a 4U multi-GPU storage-optimized system engineered for demanding enterprise AI, machine learning, and high-performance computing workloads. Built on Supermicro's AMD EPYC-based platform, the system is architected to support multiple high-performance GPUs alongside significant local NVMe storage capacity, enabling tightly coupled compute and data pipelines within a single chassis. The design philosophy prioritizes bandwidth density and thermal headroom, accommodating the power and cooling demands of modern data-center-class accelerators.

The GS-A21GPU4T integrates Supermicro's storage-optimized chassis design, offering a combination of U.2 and M.2 NVMe bays alongside traditional SATA/SAS bay options, making it well-suited for workloads where GPU compute must operate in close proximity to large, fast datasets. Dual AMD EPYC processor sockets deliver high PCIe lane counts and large memory address space, supporting the PCIe bandwidth required to keep multiple GPU accelerators fully utilized. The system supports high-capacity DDR4 registered ECC memory across multiple DIMM slots, providing the system memory headroom needed for large model training and inference tasks.

Designed for enterprise datacenter deployment across AI research, scientific simulation, and media processing environments, the GS-A21GPU4T complies with standard 19-inch rack form factors and incorporates redundant hot-swap power supplies and tool-less component access to support operational continuity in production environments. Omnixon Global supplies this system to enterprise and public-sector buyers across the UAE, GCC, EMEA, and APAC regions, supporting datacenter modernization and AI infrastructure buildouts.

Ideal for

• Large-scale deep learning model training using multi-GPU parallelism with high-throughput local NVMe storage for dataset staging
• AI inference serving at scale, leveraging multiple GPU accelerators to handle concurrent inference requests with low latency
• High-performance computing (HPC) simulations in fields such as computational fluid dynamics, genomics, and financial modeling
• Video transcoding and rendering pipelines requiring GPU acceleration combined with fast local storage for media asset management
• Data analytics and in-memory database acceleration where large EPYC-based memory capacity pairs with GPU compute offload
• Enterprise MLOps environments requiring a self-contained compute-and-storage node within a converged GPU cluster architecture

Technical specifications

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