NVIDIA-Certified Associate AI Infrastructure and Operations NCA-AIIO Question # 9 Topic 1 Discussion
NCA-AIIO Exam Topic 1 Question 9 Discussion:
Question #: 9
Topic #: 1
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?
A.
The model is too large to fit into GPU memory.
B.
The model is being used by a large number of users.
C.
The model is being used for large-scale inference workloads.
Multi-node training is advantageous when a model’s size—its parameters, activations, and gradients—exceeds the memory capacity of a single GPU. By sharding the model across multiple nodes (using techniques like data parallelism or model parallelism), training becomes feasible and efficient. User count and inference scale are unrelated to training architecture needs, which focus on compute and memory distribution.
(Reference: NVIDIA AI Infrastructure and Operations Study Guide, Section on Multi-Node Training Benefits)
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