Exam NCA-AIIO Topic 1 Question 8 Discussion

Actual exam question for NVIDIA's NCA-AIIO exam
Question #: 8
Topic #: 1
You are deploying a large-scale AI model training pipeline on a cloud-based infrastructure that uses NVIDIA GPUs. During the training, you observe that the system occasionally crashes due to memory overflows on the GPUs, even though the overall GPU memory usage is below the maximum capacity. What is the most likely cause of the memory overflows, and what should youdo to mitigate this issue?

Suggested Answer: D Vote an answer

The system encountering fragmented memory (D) is the most likely cause of memory overflows despite overall usage being below capacity. GPU memory fragmentation occurs when memory allocation/deallocation patterns (e.g., from dynamic tensor operations) leave unusable gaps, preventing allocation of contiguous blocks needed for certain operations. Enabling unified memory management (via CUDA's Unified Memory) mitigates this by allowing the system to manage memory dynamically between CPU and GPU, reducing fragmentation and overflows.
* Large batch size(A) could exceed memory, but usage below capacity suggests fragmentation, not total size, is the issue.
* Slow data pipeline(B) causes idling, not memory overflows.
* CPU overload(C) affects preprocessing, not GPU memory allocation directly.
NVIDIA's CUDA documentation recommends Unified Memory for such scenarios (D).

by Clare at Apr 23, 2025, 08:49 AM

Limited Time Offer

15%

Off

Get Premium NCA-AIIO Questions as Interactive Self Test Engine or PDF

Comments

Chosen Answer:
This is a voting comment (?) , you can switch to a simple comment.
Switch to a voting comment New
Nick name: Submit Cancel
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
0
0
0
10