300-640 Exam Dumps - Implementing Cisco Data Center AI Infrastructure (DCAI)

The Cisco UCS C885A M8 with NVIDIA H200 GPUs is purpose-built for dense accelerated computing and directly satisfies the NVLink requirement. Cisco's C885A M8 NVIDIA configuration supports eight H100 or H200 SXM Tensor Core GPUs on an HGX platform. Those GPUs are interconnected using NVIDIA NVLink, providing the high-bandwidth GPU-to-GPU communication necessary for distributed tensor processing inside the server.

The platform also provides substantial host-memory capacity, dual AMD EPYC processors, high-speed local NVMe storage, multiple 400-GbE adapters for inter-node GPU communication, and Cisco Intersight integration. These capabilities make it appropriate for large language models, generative AI training, fine-tuning, RAG, and large inference workloads.

Option A does not provide the same HGX NVLink-based eight-GPU architecture with an L40 configuration. Option B uses AMD accelerators; AMD GPU connectivity employs AMD interconnect technologies rather than NVIDIA NVLink. Option C is designed for materially different workload and GPU-density requirements and does not deliver the HGX H200 NVLink topology specified by the scenario.

The critical selection criterion is not merely whether a server can host a discrete GPU. The question explicitly requires direct GPU-to-GPU access through NVLink , which identifies the NVIDIA HGX-based C885A M8 configuration.

Study Guide Reference: AI Infrastructure Components and Architecture — compute selection based on CPU, GPU, memory, virtualization, interconnect performance, and workload requirements.

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The UCS X210c M8 combined with the UCS X580p PCIe Node satisfies the complete requirement set. The X210c M8 uses Intel Xeon 6 processors, while the X580p provides modular GPU expansion and supports up to four PCIe GPUs. Cisco specifically positions this combination for generative AI, inference, and other GPU-accelerated workloads. Management is policy-driven through Cisco Intersight, providing the required cloud-based operational model.

The X580p also supports NVIDIA H200 NVL GPUs and NVLink Bridge capabilities. This is significant where low-latency communication is required between specific GPU pairs because NVLink provides substantially higher-bandwidth GPU-to-GPU communication than standard PCIe-only communication. Cisco's UCS ordering guidance specifies that H200 NVL supports NVL Bridge configurations with a minimum of two GPUs.

Options C and D are high-density AI systems, but they use AMD EPYC-based architectures rather than satisfying the stated Intel CPU requirement. Option A likewise does not match the specified X-Series composability, cloud-managed GPU resource model, and Intel-based requirement as directly as the X210c M8 configuration.

Study Guide Reference: 2.0 AI Infrastructure Components and Architecture — 2.2 Compute deployment; 2.4 power and efficiency considerations.

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