PASS GUARANTEED LATEST NVIDIA - EXAM NCP-AIN TORRENT

Pass Guaranteed Latest NVIDIA - Exam NCP-AIN Torrent

Pass Guaranteed Latest NVIDIA - Exam NCP-AIN Torrent

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NVIDIA-Certified Professional AI Networking Sample Questions (Q67-Q72):

NEW QUESTION # 67
You have implemented adaptive routing in your Spectrum-X network to optimize AI workload performance.
You need to verify the effectiveness of this configuration and monitor its impact on network congestion.
Which tool would be most appropriate for monitoring and analyzing the adaptive routing performance in your Spectrum-X environment?

  • A. MLNXOS
  • B. NetQ
  • C. Ansible
  • D. CloudAI Benchmark

Answer: B

Explanation:
NVIDIA NetQ is a comprehensive network operations tool designed to provide real-time visibility into the health and performance of NVIDIA networking environments, including Spectrum-X. It offers detailed telemetry and analytics, allowing administrators to monitor adaptive routing behaviors, detect congestion, and analyze traffic patterns. By leveraging NetQ, you can ensure that adaptive routing is functioning as intended and that the network is optimized for AI workloads.
Reference Extracts from NVIDIA Documentation:
* "The NVIDIA NetQ network validation and ASIC monitoring tool set provide visibility into the network health and behavior. The NetQ flow telemetry analysis shows the paths that data flows take as they traverse the network, providing network latency and performance insights."
* "By leveraging telemetry from Spectrum Ethernet switches and BlueField-3 SuperNICs, NVIDIA NetQ can detect network issues proactively and troubleshoot network issues faster for optimal use of network capacity."


NEW QUESTION # 68
A high-performance InfiniBand fabric requires a routing engine that maximizes throughput and network utilization while reducing congestion. Which option below is the best routing engine for InfiniBand?

  • A. Shortest Path Routing
  • B. Round Robin Routing
  • C. Adaptive Routing
  • D. Random Routing

Answer: C

Explanation:
Adaptive Routingin InfiniBand networks dynamically selects the optimal path for data packets based on current network conditions, such as congestion levels and link utilization. This approach ensures that traffic is evenly distributed across the network, preventing bottlenecks and maximizing overall throughput.
By continuously monitoring the network and adjusting routes in real-time, Adaptive Routing enhances performance and reliability, making it the preferred choice for high-performance computing environments where consistent low latency and high bandwidth are critical.
Reference:NVIDIA InfiniBand Adaptive Routing Technology Whitepaper


NEW QUESTION # 69
You are configuring an InfiniBand network for an AI cluster and need to install the appropriate software stack. Which NVIDIA software package provides the necessary drivers and tools for InfiniBand configuration in Linux environments?

  • A. NVIDIA GPU Cloud
  • B. MLNX_OFED
  • C. NVIDIA Container Runtime
  • D. CUDA Toolkit

Answer: B

Explanation:
MLNX_OFED (Mellanox OpenFabrics Enterprise Distribution) is an NVIDIA-tested and packaged version of the OpenFabrics Enterprise Distribution (OFED) for Linux. It provides the necessary drivers and tools to support InfiniBand and Ethernet interconnects using the same RDMA (Remote Direct Memory Access) and kernel bypass APIs. MLNX_OFED enables high-performance networking capabilities essential for AI clusters, including support for up to 400Gb/s InfiniBand and RoCE (RDMA over Converged Ethernet).
Reference Extracts from NVIDIA Documentation:
* "MLNX_OFED is an NVIDIA tested and packaged version of OFED that supports two interconnect types using the same RDMA (remote DMA) and kernel bypass APIs called OFED verbs - InfiniBand and Ethernet."
* "Up to 400Gb/s InfiniBand and RoCE (based on the RDMA over Converged Ethernet standard) over 10
/25/40/50/100/200/400GbE are supported."


NEW QUESTION # 70
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. NVLink for both intra-node and inter-node GPU communication.
  • B. InfiniBand 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.

Answer: C

Explanation:
For optimal performance in multi-node, multi-GPU AI workloads:
* NVLinkprovides high-speed, low-latency communication between GPUs within the same node.
* InfiniBandoffers efficient, scalable communication between nodes in a data center.Combining these technologies ensures both intra-node and inter-node communication needs are effectively met.
Reference:NVIDIA NVLink & NVSwitch: Fastest HPC Data Center Platform


NEW QUESTION # 71
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 enable parallel data access and improve storage performance for distributed AI workloads.
  • C. To ensure data security and isolation from other network traffic.
  • D. To reduce the overall cost of the storage infrastructure.

Answer: A,B

Explanation:
Modern AI training (especially with LLMs) requires extremely high-speed, parallel access to large datasets. A dedicated storage fabricseparates data I/O traffic from the training compute path and avoids contention.
FromNVIDIA DGX Infrastructure Reference Architectures:
"Dedicated storage networks eliminate I/O bottlenecks by providing low-latency, high-bandwidth access to distributed storage for large-scale training jobs."
"Parallel access to datasets is key for performance, especially in multi-node, multi-GPU AI clusters." Security (B)is important, but not the core reason for a storage fabric.
Cost (D)is typicallyincreased, not reduced, with dedicated fabrics.
Reference: NVIDIA BasePOD/AI Infrastructure Deployment Guidelines - Storage Section


NEW QUESTION # 72
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