Q45. What is an advantage of InfiniBand over Ethernet?

Q46. In a distributed AI training environment, you notice that the GPU utilization drops significantly when the model reaches the backpropagation stage, leading to increased training time. What is the most effective way to address this issue?

Q47. How many out-of-band network management connections are in a DGX H100 system?

Q48. You are assisting in a project that involves deploying a large-scale AI model on a multi-GPU server. The server is experiencing unexpected performance degradation during inference, and you have been asked to analyze the system under the supervision of a senior engineer. Which approach would be most effective in identifying the source of the performance degradation?

Q49. When virtualizing a GPU-accelerated infrastructure, which of the following is a critical consideration to ensure optimal performance for AI workloads?

Q50. Which feature of RDMA reduces CPU utilization and lowers latency?

Q51. What is the importance of a job scheduler in an AI resource-constrained cluster?

Q52. You are part of a team working on optimizing an AI model that processes video data in real-time. The model is deployed on a system with multiple NVIDIA GPUs, and the inference speed is not meeting the required thresholds. You have been tasked with analyzing the data processing pipeline under the guidance of a senior engineer. Which action would most likely improve the inference speed of the model on the NVIDIA GPUs?

Q53. What is a significant benefit of using containers in an AI development environment?

Q54. You are part of a team analyzing the results of a machine learning experiment that involved training models with different hyperparameter settings across various datasets. The goal is to identify trends in how hyperparameters and dataset characteristics influence model performance, particularly accuracy and overfitting. Which analysis method would best help in identifying the relationships between hyperparameters, dataset characteristics, and model performance?

Q55. What aspect of AI infrastructure design is MOST critical for ensuring high availability of production AI services during hardware or node failures?

Q56. Which of the following statements is true about GPUs and CPUs?

Q57. The data center administrator is asked to deploy infrastructure to support training of a large natural language processing model with a billion parameters and they need the fastest method to train the model. What should the administrator recommend to support this?

Q58. How is the architecture different in a GPU versus a CPU?

Q59. Your organization operates an AI cluster where various deep learning tasks are executed. Some tasks are time- sensitive and must be completed as soon as possible, while others are less critical. Additionally, some jobs can be parallelized across multiple GPUs, while others cannot. You need to implement a job scheduling policy that balances these needs effectively. Which scheduling policy would best balance the needs of time-sensitive tasks and efficiently utilize the available GPUs?

Q60. You are assisting a senior data scientist in a project aimed at improving the efficiency of a deep learning model. The team is analyzing how different data preprocessing techniques impact the model’s accuracy and training time. Your task is to identify which preprocessing techniques have the most significant effect on these metrics. Which method would be most effective in identifying the preprocessing techniques that significantly affect model accuracy and training time?

Q61. What is a key value of using NVIDIA NIMs?

Q62. A financial institution is deploying two different machine learning models to predict credit defaults. The models are evaluated using Mean Squared Error (MSE) as the primary metric. Model A has an MSE of 0.015, while Model B has an MSE of 0.027. Additionally, the institution is considering the complexity and interpretability of the models. Given this information, which model should be preferred and why?

Q63. How many Mellanox ConnectX-6 Single Port VPI cards are in a DGX A100 system?

Q64. A retail company wants to implement an AI-based system to predict customer behavior and personalize product recommendations across its online platform. The system needs to analyze vast amounts of customer data, including browsing history, purchase patterns, and social media interactions. Which approach would be the most effective for achieving these goals?

Q65. Which of the following statements is true about Kubernetes orchestration?

Q66. Which of the following statements correctly differentiates between AI, Machine Learning, and Deep Learning?

Q67. A large healthcare provider wants to implement an AI-driven diagnostic system that can analyze medical images across multiple hospitals. The system needs to handle large volumes of data, comply with strict data privacy regulations, and provide fast, accurate results. The infrastructure should also support future scaling as more hospitals join the network. Which approach using NVIDIA technologies would best meet the requirements for this AI-driven diagnostic system?

Q68. How is out-of-band management utilized by network operators in an AI environment?

Q69. In a large-scale AI training environment, a data scientist needs to schedule multiple AI model training jobs with varying dependencies and priorities. Which orchestration strategy would be most effective to ensure optimal resource utilization and job execution order?