Question 1

Which feature of RDMA reduces CPU utilization and lowers latency?

Options :

A : Increased memory buffer size.

B : Network adapters that include hardware offloading.

C : NVIDIA Magnum I/O software.

Answer: B

Question 2

Which two components are included in GPU Operator? (Choose two.)

Options :

A : Drivers

B : PyTorch

C : DCGM

D : TensorFlow

Answer: A,C

Question 3

You are part of a team investigating the performance variability of an AI model across different hardware configurations. The model is deployed on various servers with differing GPU types, memory sizes, and CPU clock speeds. Your task is to identify which hardware factors most significantly impact the model's inference time. Which analysis approach would be most effective in identifying the hardware factors that significantly impact the model’s inference time?

Options :

A : Conduct a t-test comparing inference times between two different GPU types.

B : Perform a multiple regression analysis with inference time as the dependent variable.

C : Apply clustering to group hardware configurations by inference time.

D : Create a bar chart comparing average inference times across hardware configurations.

Answer: B

Question 4

You are assisting a senior engineer in analyzing the results of an experiment that tested multiple configurations of an AI model on different datasets. The goal is to identify any relationships between the dataset characteristics (such as size, type, and quality) and the model's performance metrics. You need to find which factors most significantly impact the model’s accuracy. Which approach would be most effective for identifying the factors that most significantly impact the model's accuracy?

Options :

A : Apply PCA (Principal Component Analysis) on the model-s performance metrics.

B : Perform a correlation analysis between dataset characteristics and accuracy.

C : Create a histogram of accuracy scores for each dataset.

D : Use a pie chart to display the proportion of datasets that achieved high accuracy.

Answer: B

Question 5

A company is deploying a large-scale AI training workload that requires distributed computing across multiple GPUs. They need to ensure efficient communication between GPUs on different nodes and optimize the training time. Which of the following NVIDIA technologies should they use to achieve this?

Options :

A : NVIDIA NVLink

B : NVIDIA TensorRT

C : NVIDIA NCCL (NVIDIA Collective Communication Library)

D : NVIDIA DeepStream SDK

Answer: C

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