NCP-AIO Installation and Deployment Practice Question
What is the primary function of the NVIDIA Persistence Daemon in an AI deployment?
⚠ Common exam trap
Candidates often think the persistence daemon is used for saving machine learning model checkpoints, confusing storage persistence with driver state persistence.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
It keeps the GPU driver initialized to reduce latency during application startup.
The Persistence Daemon ensures that the NVIDIA driver remains loaded even when no applications are using the GPU. This prevents the driver from unloading and then reloading when a job starts, which significantly reduces the startup latency of AI models. It is a critical configuration for high-performance environments where frequent job scheduling would otherwise incur unnecessary overhead from repeated driver and device initialization.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It automatically updates the NVIDIA driver when a new version is released on the web.
Why it's wrong here
The Persistence Daemon is not an update manager. Automatic updates in production clusters are dangerous and should be handled by a controlled deployment process, such as Ansible or image-based provisioning, to prevent unexpected downtime and ensure compatibility across all nodes in the cluster.
- ✓
It keeps the GPU driver initialized to reduce latency during application startup.
Why this is correct
By maintaining the driver's state in memory, the Persistence Daemon eliminates the overhead associated with the driver unloading and reloading process. This ensures that GPU resources are always ready for immediate use, which is essential for performance-sensitive AI applications that require rapid task execution.
- ✗
It monitors GPU health and automatically initiates a reboot if an error is detected.
Why it's wrong here
Monitoring and recovery are handled by higher-level management software like Base Command or custom scripts. The daemon's scope is restricted to driver state management, not hardware health monitoring or autonomous system recovery, as automatic reboots could inadvertently disrupt running training jobs on other GPUs.
- ✗
It manages the network traffic between the GPU and the storage backend.
Why it's wrong here
Data movement is handled by the networking stack and high-level libraries like NCCL or GPUDirect. The Persistence Daemon is strictly concerned with the driver's state and does not participate in network I/O or storage management operations, which occur at the protocol and application level.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official NVIDIA exam blueprint
This NCP-AIO practice question is part of Courseiva's free NVIDIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the NCP-AIO exam.