최신 NCA-AIIO 무료덤프 - NVIDIA-Certified Associate AI Infrastructure and Operations
Your company is running a distributed AI application that involves real-time data ingestion from IoT devices spread across multiple locations. The AI model processing this data requires high throughput and low latency to deliver actionable insights in near real-time. Recently, the application has been experiencing intermittent delays and data loss, leading to decreased accuracy in the AI model's predictions. Which action would best improve the performance and reliability of the AI application in this scenario?
정답: C
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Your AI data center is running multiple high-performance GPU workloads, and you notice that certain servers are being underutilized while others are consistently at full capacity, leading to inefficiencies. Which of the following strategies would be most effective in balancing the workload across your AI data center?
정답: D
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Your team is tasked with accelerating a large-scale deep learning training job that involves processing a vast amount of data with complex matrix operations. The current setup uses high-performance CPUs, but the training time is still significant. Which architectural feature of GPUs makes them more suitable than CPUs for this task?
정답: B
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Your company is building an AI-powered recommendation engine that will be integrated into an e-commerce platform. The engine will be continuously trained on user interaction data using a combination of TensorFlow, PyTorch, and XGBoost models. You need a solution that allows you to efficiently share datasets across these frameworks, ensuring compatibility and high performance on NVIDIA GPUs. Which NVIDIA software tool would be most effective in this situation?
정답: D
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In your AI data center, you need to ensure continuous performance and reliability across all operations. Which two strategies are most critical for effective monitoring? (Select two)
정답: A,C
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When implementing an MLOps pipeline, which component is crucial for managing version control and tracking changes in model experiments?
정답: A
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You are assisting a senior data scientist in optimizing a distributed training pipeline for a deep learning model.
The model is being trained across multiple NVIDIA GPUs, but the training process is slower than expected.
Your task is to analyze the data pipeline and identify potential bottlenecks. Which of the following is the most likely cause of the slower-than-expected training performance?
The model is being trained across multiple NVIDIA GPUs, but the training process is slower than expected.
Your task is to analyze the data pipeline and identify potential bottlenecks. Which of the following is the most likely cause of the slower-than-expected training performance?
정답: C
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During AI model deployment, your team notices significant performance degradation in inference workloads.
The model is deployed on an NVIDIA GPU cluster with Kubernetes. Which of the following could be the most likely cause of the degradation?
The model is deployed on an NVIDIA GPU cluster with Kubernetes. Which of the following could be the most likely cause of the degradation?
정답: B
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A financial institution is using an NVIDIA DGX SuperPOD to train a large-scale AI model for real-time fraud detection. The model requires low-latency processing and high-throughput data management. During the training phase, the team notices significant delays in data processing, causing the GPUs to idle frequently.
The system is configured with NVMe storage, and the data pipeline involves DALI (Data Loading Library) and RAPIDS for preprocessing. Which of the following actions is most likely to reduce data processing delays and improve GPU utilization?
The system is configured with NVMe storage, and the data pipeline involves DALI (Data Loading Library) and RAPIDS for preprocessing. Which of the following actions is most likely to reduce data processing delays and improve GPU utilization?
정답: B
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Which component of the NVIDIA AI software stack is primarily responsible for optimizing deep learning inference performance by leveraging the specific architecture of NVIDIA GPUs?
정답: B
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