最新的NVIDIA AI Operations - NCP-AIO免費考試真題
What is the primary purpose of feature stores in AI operations pipelines when managing machine learning workflows across multiple teams and production systems?
正確答案: D
說明：（僅 Fast2test 成員可見）
An administrator requires full access to the NGC Base Command Platform CLI.
Which command should be used to accomplish this action?
Which command should be used to accomplish this action?
正確答案: B
說明：（僅 Fast2test 成員可見）
Which approach involves running a new model in parallel with the existing production model without affecting user-facing predictions to evaluate its performance in real-time conditions?
正確答案: A
說明：（僅 Fast2test 成員可見）
What is the key purpose of a model registry in AI operations when managing multiple versions of machine learning models across teams and environments?
正確答案: C
說明：（僅 Fast2test 成員可見）
What technique is commonly used in AI operations to detect when the statistical distribution of incoming data differs significantly from the training dataset, potentially affecting model predictions and requiring intervention?
正確答案: A
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An instance of NVIDIA Fabric Manager service is running on an HGX system with KVM. A System Administrator is troubleshooting NVLink partitioning.
By default, what is the GPU polling subsystem set to?
By default, what is the GPU polling subsystem set to?
正確答案: A
說明：（僅 Fast2test 成員可見）
You are monitoring the resource utilization of a DGX SuperPOD cluster using NVIDIA Base Command Manager (BCM). The system is experiencing slow performance, and you need to identify the cause.
What is the most effective way to monitor GPU usage across nodes?
What is the most effective way to monitor GPU usage across nodes?
正確答案: A
說明：（僅 Fast2test 成員可見）
You are deploying an AI workload on a Kubernetes cluster that requires access to GPUs for training deep learning models. However, the pods are not able to detect the GPUs on the nodes.
What would be the first step to troubleshoot this issue?
What would be the first step to troubleshoot this issue?
正確答案: D
說明：（僅 Fast2test 成員可見）
You are managing a Kubernetes cluster running AI training jobs using TensorFlow. The jobs require access to multiple GPUs across different nodes, but inter-node communication seems slow, impacting performance.
What is a potential networking configuration you would implement to optimize inter-node communication for distributed training?
What is a potential networking configuration you would implement to optimize inter-node communication for distributed training?
正確答案: D
說明：（僅 Fast2test 成員可見）