NVIDIA-Certified Associate AI Infrastructure and Operations Questions and Answers
Question 13
What is a common tool for container orchestration in AI clusters?
Options:
A.
Kubernetes
B.
MLOps
C.
Slurm
D.
Apptainer
Answer:
A
Explanation:
Kubernetes is the industry-standard tool for container orchestration in AI clusters, automating deployment, scaling, and management of containerized workloads. Slurm manages job scheduling, Apptainer (formerly Singularity) runs containers, and MLOps is a practice, not a tool, making Kubernetes the clear leader in this domain.
(Reference: NVIDIA AI Infrastructure and Operations Study Guide, Section on Container Orchestration)
Question 14
In a data center, what is the purpose and benefit of a DPU?
Options:
A.
A DPU is responsible for providing backup and disaster recovery solutions.
B.
A DPU is used for managing physical infrastructure, such as power and cooling.
C.
A DPU is responsible for managing network connections and security.
D.
A DPU is designed to offload, accelerate, and isolate infrastructure workloads.
Answer:
D
Explanation:
A Data Processing Unit (DPU) is a programmable processor that offloads, accelerates, and isolates infrastructure workloads—like networking, storage, and security—from the CPU. This enhances performance, reduces CPU overhead, and improves security by segregating tasks, benefiting AI data centers. It doesn’t handle backups or physical infrastructure directly, focusing instead on compute efficiency.
For which workloads is NVIDIA Merlin typically used?
Options:
A.
Recommender systems
B.
Natural language processing
C.
Data analytics
Answer:
A
Explanation:
NVIDIA Merlin is a specialized, end-to-end framework engineered for building and deploying large-scale recommender systems. It streamlines the entire pipeline, including data preprocessing (e.g., feature engineering, data transformation), model training (using GPU-accelerated frameworks), and inference optimizations tailored for recommendation tasks. Unlike general-purpose tools for natural language processing or data analytics, Merlin is optimized to handle the unique challenges of recommendation workloads, such as processing massive user-item interaction datasets and delivering personalized results efficiently.
