NCA-GENL Software Development Practice Question
Exhibit
log_output: [INFO] Loading model 'llama_v3'... [ERROR] CUDA error: all CUDA-capable devices are busy or unavailable.
Refer to the exhibit. An engineer receives this error during deployment. What is the most likely cause?
⚠ Common exam trap
Candidates often mistake hardware memory exhaustion errors for software configuration issues or missing library dependencies, ignoring the direct system message indicating that another active process currently occupies the target GPU.
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
✓
Another process is already using the target GPU.
The error indicates that another process or container has locked the GPU device, preventing the Triton server from initializing the model. In production environments, managing GPU resource allocation is crucial. If multiple processes compete for the same hardware without proper resource isolation, initialization will fail, causing downtime. Resolving this requires checking for conflicting processes or ensuring proper container resource limits to prevent GPU resource contention.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model file is corrupted and missing.
Why it's wrong here
A corrupted file would trigger a file-not-found or checksum error, not a CUDA busy error. The CUDA error specifically points to a hardware-software contention issue where the GPU driver is unable to provide the necessary resources because they are already in use by another task.
- ✓
Another process is already using the target GPU.
Why this is correct
This error is the standard response when the GPU is locked by another application or container. In a multi-tenant environment, this often happens if resources are not correctly partitioned, preventing the current inference service from acquiring the device handle required to load the model into VRAM.
- ✗
The system lacks the required RAM for the CPU.
Why it's wrong here
Insufficient system RAM would result in a standard application crash or an out-of-memory error from the operating system, not a specific CUDA device busy error. The CUDA error is strictly related to GPU-specific resource contention between the driver and the process attempting to access it.
- ✗
The model version is incompatible with the server.
Why it's wrong here
Version incompatibility would lead to a configuration error or an internal loading exception during the model initialization process. It does not manifest as a hardware-busy error, which indicates that the device itself is unavailable for any operation regardless of the model's validity or compatibility.
Visual reference
About these practice questions
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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 NCA-GENL 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 NCA-GENL exam.