New NCP-AIO Exam Cram & NCP-AIO Valid Dumps Files

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NVIDIA NCP-AIO Exam Questions With PDF File Format

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NVIDIA AI Operations Sample Questions (Q227-Q232):

NEW QUESTION # 227
You are deploying a Deep Learning model as a service using Triton Inference Server within a VMI container on Google Cloud Platform (GCP). You want to leverage TensorRT for optimized inference performance. Which of the following steps are necessary to ensure TensorRT is properly configured and used?

A. Ensure the Triton Inference Server container image includes the necessary TensorRT libraries and dependencies.
B. Specify the 'optimization' parameter as 'TRT in the model configuration file Cconfig.pbtxt) for Triton.
C. Configure the GCP instance with an NVIDIA GPU that supports TensorRT.
D. No special configuration is needed; Triton automatically detects and uses TensorRT if available.
E. Convert the model to a TensorRT engine using 'trtexec' command before loading it into Triton.

Answer: A,B,C,E

Explanation:
To leverage TensorRT with Triton, you need to ensure the container has the libraries, convert the model to a TensorRT engine, specify the optimization parameter in the model configuration, and use a GPU that supports TensorRT. Each of these steps is crucial for proper TensorRT utilization.

NEW QUESTION # 228
You are tasked with implementing a data lake for AI training. The data lake must support various data formats (e.g., images, text, tabular data) and be accessible by multiple AI frameworks (e.g., TensorFlow, PyTorch). Which of the following technologies and storage characteristics are most suitable for this data lake?

A. Hadoop Distributed File System (HDFS) with Parquet or ORC file formats.
B. Object storage (e.g., AWS S3, Azure Blob Storage) with support for data partitioning and a metadata catalog (e.g., AWS Glue, Apache Hive Metastore).
C. A traditional relational database management system (RDBMS) with a fixed schema.
D. Tape Archival system.
E. A NoSQL database system optimized for key-value storage.

Answer: A,B

Explanation:
HDFS with columnar file formats like Parquet and ORC is a common choice for data lakes due to its scalability and support for various data formats. Object storage with data partitioning and a metadata catalog provides a flexible and cost-effective alternative, allowing for efficient data discovery and access. RDBMS systems are not well-suited for unstructured data or changing schemas. NoSQL databases may be suitable for certain types of data, but not as a general-purpose data lake solution. Tape systems are not appropriate for general-purpose data lakes.

NEW QUESTION # 229
You are developing a DOCA application that needs to handle network packets at line rate. Which of the following DOCA services would be most suitable for achieving this goal and why?

A. DOCA RegEx: Offers regular expression matching for packet filtering but can introduce latency at high traffic rates.
B. DOCA Flow: Allows defining complex flow rules and offloading packet processing to the DPU hardware, achieving high performance.
C. DOCA Telemetry: Designed for monitoring and collecting network statistics rather than packet processing.
D. DOCA SPP: Provides support for scalable packet processing by managing packet buffers in user space but requires careful resource management.
E. DOCA DPI: Provides deep packet inspection capabilities for analyzing packet content but is not optimized for line-rate processing.

Answer: B,D

Explanation:
DOCA Flow is designed for high-performance packet processing and allows offloading flow rules to the DPU hardware. DOCA SPP also plays a crucial role in line-rate processing with efficient packet buffer management.

NEW QUESTION # 230
You are designing storage for an AI model that performs real-time object detection on streaming video. Which of the following storage characteristics are most important?

A. Low latency for accessing video frames during inference.
B. Support for cold storage.
C. Data deduplication for minimizing storage costs.
D. Large capacity for long-term video archival.
E. High sustained write throughput for incoming video streams.

Answer: A,E

Explanation:
Real-time object detection requires both the ability to ingest incoming video streams quickly (high write throughput) and access frames with minimal delay (low latency) for inference. Long-term archival and deduplication are less critical for real-time performance. Cold storage is not relevant in the operational data flow.

NEW QUESTION # 231
You are tuning the storage performance of a Kubernetes cluster that uses Longhorn as the storage backend. You've noticed inconsistent read latencies. What Longhorn specific configurations could you adjust to potentially improve the consistency and reduce latency for read operations?

A. Adjust the 'replica-auto-balance' setting to redistribute replicas more evenly across nodes.
B. Enable 'data locality' to ensure that replicas are preferably placed on the same node as the pod accessing the volume, reducing network latency.
C. Increase the number of replicas for each Longhorn volume to improve data redundancy and read parallelism.
D. Disable Longhorn's built-in monitoring to reduce overhead.
E. Reduce the size of the Longhorn volumes to decrease the amount of data that needs to be read.

Answer: A,B,C

Explanation:
More replicas increase read parallelism. 'replica-auto-balance' ensures replicas are well-distributed. 'data locality minimizes network hops for reads. It is not beneficial to reduce volume size, as that is required. Disabling built-in monitoring is also a bad idea.

NEW QUESTION # 232
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New NCP-AIO Exam Cram & NCP-AIO Valid Dumps Files

NVIDIA NCP-AIO Exam Questions With PDF File Format

NVIDIA AI Operations Sample Questions (Q227-Q232):

Three Formats for NCP-AIO Practice Tests Prep4sures Exam Prep Solutions

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