NCP-AIN 무료 덤프문제 온라인 액세스

You are optimizing an AI workload that involves multiple GPUs across different nodes in a data center. The application requires both high-bandwidth GPU-to-GPU communication within nodes and efficient communication between nodes.
Which combination of NVIDIA technologies would best support this multi-node, multi-GPU AI workload?

• A.InfiniBand for both intra-node and inter-node GPU communication.
• B.NVLink for both intra-node and inter-node GPU communication.
• C.NVLink for intra-node GPU communication and InfiniBand for inter-node communication.
• D.PCIe for intra-node GPU communication and RoCE for inter-node communication.

What are the prerequisites for performing Flow Analysis with NetQ?

• A.Cumulus 5.x and later / Spectrum-2 and later / On-premises deployment
• B.Cumulus 5.x and later / Spectrum-2 and later / LCM enabled
• C.Cumulus 5.x and later / Spectrum-3 and later / On-premises deployment
• D.Cumulus 4.x and later / Spectrum-2 and later / LCM enabled

When creating a simu-lation in NVIDIA AIR, what syntax would you use to define a link between port 1 on spine-01 and port 41 on gpu-leaf-01?

• A."spine-01":"eth1" - "gpu-leaf-01":"eth41"
• B."spine-01":"swp1" to "gpu-leaf-01":"swp41"
• C."spine-01 'eth1" to "gpu-leaf-01":"eth41"
• D."spine-01":*swp01" - *gpu-leaf-01":"swp41"

A leading AI research center is upgrading its infrastructure to support large language model projects.
The team is debating whether to implement a dedicated storage fabric for their AI workloads.
Which of the following best explains why a dedicated storage fabric is crucial for this AI network architecture?
Pick the 2 correct responses below

• A.To provide high-bandwidth, low-latency data access that prevents I/O bottlenecks during AI model training.
• B.To ensure data security and isolation from other network traffic.
• C.To enable parallel data access and improve storage performance for distributed AI workloads.
• D.To reduce the overall cost of the storage infrastructure.

You have recently implemented NVIDIA Spectrum-X in your data center to optimize AI workloads. You need to verify the performance improvements and create a baseline for future comparisons.
Which tool would be most appropriate for creating performance baseline results in this Spectrum-X environment?

• A.MLNX-OS
• B.CloudAI Benchmark
• C.NetQ
• D.Ansible