Exam NCA-GENL Topic 3 Question 59 Discussion

Actual exam question for NVIDIA's NCA-GENL exam
Question #: 59
Topic #: 3

You are using RAPIDS and Python for a data analysis project. Which pair of statements best explains how RAPIDS accelerates data science?

A. RAPIDS enables on-GPU processing of computationally expensive calculations and minimizes CPU- GPU memory transfers. B. RAPIDS is a Python library that provides functions to accelerate the PCIe bus throughput via word- doubling. C. RAPIDS provides lossless compression of CPU-GPU memory transfers to speed up data analysis.

Suggested Answer: A Vote an answer

RAPIDS is a suite of open-source libraries designed to accelerate data science workflows by leveraging GPU processing, as emphasized in NVIDIA's Generative AI and LLMs course. It enables on-GPU processing of computationally expensive calculations, such as data preprocessing and machine learning tasks, using libraries like cuDF and cuML. Additionally, RAPIDS minimizes CPU-GPU memory transfers by performing operations directly on the GPU, reducing latency and improving performance. Options A and B are identical and correct, reflecting RAPIDS' core functionality. Option C is incorrect, as RAPIDS does not focus on PCIe bus throughput or "word-doubling," which is not a relevant concept. Option D is wrong, as RAPIDS does not rely on lossless compression for acceleration but on GPU-parallel processing. The course notes: "RAPIDS accelerates data science by enabling GPU-based processing of computationally intensive tasks and minimizing CPU-GPU memory transfers, significantly speeding up workflows." References: NVIDIA Building Transformer-Based Natural Language Processing Applications course; NVIDIA Introduction to Transformer-Based Natural Language Processing.

by Samantha at Nov 25, 2025, 02:24 AM

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