Brand: Huawei | Category: GPUs
SKU: H-ATLAS-900-A3 | Part #: Atlas-900-A3 | MPN: Atlas-900-A3
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Enterprise AI training and inference workloads demand purpose-built acceleration architecture, and the Huawei Atlas 900 A3 AI Cluster Node delivers exactly that through its eight Huawei Ascend 910B NPUs per node, each powered by the Da Vinci 3rd Generation architecture. This rack-mountable cluster node is engineered for sovereign AI infrastructure and enterprise data center deployments where distributed training at scale is non-negotiable. The system supports multiple AI compute precisions—FP16, BF16, and INT8—enabling flexible optimization across diverse model architectures and inference scenarios.
For AI infrastructure teams and enterprise procurement specialists evaluating sovereign AI solutions, the Atlas-900-A3 combines intra-node coherence via HCCS (Huawei Cache Coherence System) high-bandwidth fabric with high-speed optical cluster interconnect for seamless multi-node scale-out. The software stack includes CANN (Compute Architecture for Neural Networks), and the node supports leading frameworks—MindSpore, PyTorch, and TensorFlow via CANN adapter layer—across EulerOS and compatible Linux distributions within the Huawei ecosystem. Active liquid or forced-air cooling options ensure sustained performance in data center environments, while integrated BMC with remote management support simplifies operational oversight. In stock at Omnixon Global, the Atlas 900 A3 is ready for immediate deployment.
Contact Omnixon Global for detailed specifications, cluster architecture planning, and an RFQ response within 48 hours.
| Brand | Huawei |
| Category | GPUs |
| SKU | H-ATLAS-900-A3 |
| Part Number | Atlas-900-A3 |
| Condition | New |
| Manufacturer Part Number | Atlas-900-A3 |
| Product Line | Atlas 900 Series |
| AI Accelerator | Huawei Ascend 910B NPU |
| NPU Architecture | Da Vinci (3rd Generation) |
| NPUs per Node | 8 |
| AI Compute Precision | FP16, BF16, INT8 |
| Inter-NPU Interconnect | HCCS (Huawei Cache Coherence System), high-bandwidth intra-node fabric |
| Network Interconnect | High-speed optical cluster interconnect for multi-node scale-out |
| Software Stack | CANN (Compute Architecture for Neural Networks) |
| Supported AI Frameworks | MindSpore, PyTorch, TensorFlow (via CANN adapter layer) |
| Form Factor | Cluster Node (rack-mountable) |
| Target Deployment | Enterprise AI data center, sovereign AI infrastructure |
| Cooling | Active liquid or forced-air cooling (data center grade) |
| Cluster Scalability | Designed for multi-node scale-out within Atlas 900 A3 cluster architecture |
| Operating System Support | EulerOS, Linux distributions supported via Huawei ecosystem |
| Management Interface | Integrated BMC with remote management support |
| Availability | In stock at Omnixon Global; RFQ response within 48 hours |
The Huawei Atlas 900 A3 AI Cluster Node accelerates AI/ML training, inference, scientific HPC, and virtualization (vGPU) workloads. Typical deployments include LLM training clusters, computer-vision pipelines, financial risk modeling, and rendering farms.
The Huawei Atlas 900 A3 AI Cluster Node is a brand new gpus product manufactured by Huawei. It has the SKU H-ATLAS-900-A3 and part number Atlas-900-A3. This enterprise-grade product is available from Omnixon Global.
Key specifications for the Huawei Atlas 900 A3 AI Cluster Node: 3 years support; new condition; support 3 years standard (manufacturer); ai optimized Yes. Manufacturer part number Atlas-900-A3. For the full datasheet with electrical, environmental, and compliance details, contact our pre-sales engineering team.
The key specifications of the Huawei Atlas 900 A3 AI Cluster Node include: support: 3 years standard (manufacturer), AI Optimized: Yes. For complete specifications and technical documentation, please contact our sales team.
The Huawei Atlas 900 A3 AI Cluster Node requires a PCIe Gen4 or Gen5 x16 slot, server power adequate for the card's TDP, and CUDA/ROCm driver support in your hypervisor or bare-metal OS. Sales engineering will confirm chassis fit (1U/2U/4U), PCIe lane count, and PSU headroom before quoting.