Determine the Benefits of SuperPOD Architectures with NetApp CERTIFIED-AI-EXPERT Practice Questions (Page 3)

Questions 11–15

1. 11foundation · easy

   Which components are the primary building blocks of an NVIDIA SuperPOD architecture?

   • ACompute nodes, a management network, and backup appliances
   • BGPU servers, a standard Ethernet LAN, and direct-attached storage
   • CCompute nodes, a high-speed network fabric, and storage systems
   • DStorage systems, a low-latency network, and virtualization software
   Reveal Solution Discussion Select an answer first
2. 12application · medium

   A financial services firm runs a SuperPOD for fraud-detection model training. Compliance requires that all training datasets be retained for 7 years, but the team needs to free up high-performance NVMe capacity for active jobs. The data is accessed rarely after the initial training run. Which NetApp data management feature should the admin use to meet both the retention policy and the performance-capacity need?

   • AReplicate the dataset to a NetApp FabricPool on a remote ONTAP cluster.
   • BCreate a Snapshot copy of the dataset and delete the active volume immediately.
   • CEnable compression on the volume to shrink the dataset so it fits on the NVMe tier.
   • DConfigure FabricPool to tier cold training datasets from the all-flash aggregate to object storage.
   Reveal Solution Discussion Select an answer first
4. 13foundation · easy

   What is a key characteristic of NetApp storage that makes it suitable for SuperPOD AI workloads?

   • AIt is limited to a single node, simplifying management
   • BIt provides only block storage, which is ideal for AI
   • CIt requires manual data tiering to optimize performance
   • DIt delivers high throughput and low latency to keep GPUs fed with data
   Reveal Solution Discussion Select an answer first
5. 14expert · hard

   A SuperPOD is experiencing slow training performance. The admin suspects storage is the bottleneck. The training job reads a 10TB dataset sequentially each epoch. The storage system shows high latency but low IOPS. Which adjustment is most likely to improve performance?

   • AMove the training dataset to a volume with a smaller block size.
   • BIncrease the number of QoS policy groups to allow more concurrent I/O.
   • CEnable inline compression on the training volume.
   • DIncrease the read-ahead (prefetch) settings on the NetApp storage for the training volume.
   Reveal Solution Discussion Select an answer first
6. 15application · medium

   A startup is evaluating whether to build a SuperPOD for their NLP models. They have a limited budget and need to scale from 32 to 128 GPUs over two years. They are concerned about the upfront cost of a full SuperPOD. Which aspect of SuperPOD with NetApp makes this incremental growth feasible?

   • AThe GPU nodes are the only component that can be added incrementally; storage and network are fixed.
   • BThe modular design allows adding compute and storage nodes in predictable increments without redesigning the network.
   • CThe network fabric must be replaced entirely when adding more than 64 GPUs.
   • DThe storage must be fully provisioned upfront to support the maximum GPU count.
   Reveal Solution Discussion Select an answer first