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NVIDIA AI Infrastructure and Operations NCA-AIIO Dumps in PDF

Free NVIDIA NCA-AIIO Real Questions (page: 15)

NCA-AIIO PDF — 116 Questions

Which type of GPU core was specifically designed to realistically simulate the lighting of a scene?

  1. Tensor Cores
  2. CUDA Cores
  3. Ray Tracing Cores

Answer(s): C

Explanation:

Ray Tracing Cores are specialized hardware units designed to accelerate the computation of ray-scene intersections and shading calculations, enabling real-time, photorealistic lighting and reflections.



Which GPUs should be used when training a neural network for self-driving cars?

  1. NVIDIA H100 GPUs
  2. NVIDIA L4 GPUs
  3. NVIDIA DRIVE Orin

Answer(s): A

Explanation:

NVIDIA H100 GPUs deliver the massive compute throughput and high-bandwidth memory needed to train the large, compute-intensive neural networks used in autonomous driving.



A customer is evaluating an AI cluster for training and is questioning why they should use a large number of nodes.
Why would multi-node training be advantageous?

  1. The model is too large to fit into GPU memory
  2. The model is being used by a large number of users
  3. The model is being used for large scale inference workloads

Answer(s): A

Explanation:

Multi-node training lets you shard and distribute model parameters across GPUs on different servers, enabling you to train models that exceed the memory capacity of any single GPU.



When should RoCE be considered to enhance network performance in a multi-node AI computing environment?

  1. A network that experiences a high packet loss rate (PLR).
  2. A network with large amounts of storage traffic.
  3. A network that cannot utilize the full available bandwidth due to high CPU utilization.

Answer(s): C

Explanation:

RoCE offloads transport work to the NIC via RDMA, cutting CPU overhead and unlocking the full link bandwidth when high CPU usage would otherwise throttle network throughput.



Which are three key features of InfiniBand networking technology?

  1. High reliability, high latency, and CPU offloads.
  2. High latency, high reliability, and high bandwidth.
  3. GPU offloads, low latency, high reliability.
  4. Low latency, high bandwidth, and CPU offloads.

Answer(s): D

Explanation:

InfiniBand delivers microsecond-class, low latency; multi-100 Gb/s (and beyond) high bandwidth; and offloads transport work (via RDMA) from the CPU, maximizing system efficiency.



An IT Professional is considering whether to implement an on-prem or cloud infrastructure.
Which of the following is a key advantage of on-prem infrastructure?

  1. Lower upfront costs and capital expenditure
  2. Scalability and flexibility
  3. Ensure data security and sovereignty
  4. Easy remote management.

Answer(s): C

Explanation:

On-premises deployments give organizations direct control over their hardware and data, making it easier to meet strict security, compliance, and sovereignty requirements.



Which feature of RDMA reduces CPU utilization and lowers latency?

  1. Increased memory buffer size.
  2. Network adapters that include hardware offloading.
  3. NVIDIA Magnum I/O software.

Answer(s): B

Explanation:

RDMA-capable network adapters offload data transfer tasks into the NIC hardware, bypassing the CPU for memory copies and transport operations - thereby reducing CPU utilization and achieving lower latency.



What is one key advantage that Cloud GPU Infrastructure has over On-Prem GPU infrastructure?

  1. Lower cost barrier to entry.
  2. Reduced cost of I/O traffic.
  3. Greater flexibility for hardware orchestration.

Answer(s): A

Explanation:

Cloud GPU offerings eliminate large capital expenditures by letting you pay-as-you-go, significantly lowering the cost barrier to getting started with high-performance GPU compute.



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