Exam NCP-ADS Topic 1 Question 220 Discussion

Actual exam question for NVIDIA's NCP-ADS exam
Question #: 220
Topic #: 1

You are working with large datasets in cuDF and have noticed significant performance bottlenecks due to repeated computation and excessive shuffling in your workflow. You want to use data caching to optimize the execution plan and reduce redundant operations.
Which of the following is the best way to implement data caching in cuDF to avoid repeated recomputation and excessive shuffling?

A. Use the .reset_index() method after performing transformations to force materialization of the dataset and cache results. B. Use the .persist() method on a cuDF DataFrame to store intermediate results in GPU memory, reducing redundant calculations. C. Use the .to_pandas() method to convert the cuDF DataFrame into a Pandas DataFrame, leveraging CPU caching instead of GPU caching. D. Store intermediate DataFrames as temporary CSV files on disk and reload them when needed to simulate a cache.

Comments

0 Happy Clients

0 Shares

0 Demo Downloads

10 Years in Business