NCP-AII Exam Dumps | An AI operations team enables Multi-Instance GPU (MIG) on several NVIDIA GPUs to improve resource utilization.

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An AI operations team enables Multi-Instance GPU (MIG) on several NVIDIA GPUs to improve resource utilization. Shortly afterward, one data science team reports that its distributed training job runs noticeably slower than before. The cluster administrator must determine the most likely reason for this behavior.

A. MIG increases GPU memory bandwidth for every workload.

B. MIG divides one physical GPU into isolated compute instances with dedicated resources.

C. MIG automatically enables NVLink aggregation across all GPU instances.

D. MIG combines multiple physical GPUs into one logical accelerator.

Correct Answer: B

MIG partitions a single GPU into multiple isolated instances, each receiving dedicated compute cores, memory, cache, and bandwidth. Although this improves utilization and workload isolation, each partition has fewer resources than the full GPU. Large distributed training workloads typically perform better using complete GPUs instead of smaller MIG instances.

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