NCP-AIO Troubleshooting and Optimization Practice Question
A team is profiling a distributed training job using NVIDIA NCCL for inter-GPU communication on a DGX A100 system. They observe that all-reduce operations are taking longer than expected, and the NCCL debug logs show frequent 'NVLS' (NVLink SHARP) errors. Which action should be taken to resolve the issue?
⚠ Common exam trap
The trap here is assuming that increasing buffer size or changing algorithms will fix NVLS errors, when the correct approach is to disable the failing feature.
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
✓
Disable NVLink SHARP by setting NCCL_NVLS_ENABLE=0 in the environment and restart the job.
NVLS errors indicate that the NVLink SHARP acceleration is failing, likely due to hardware or software incompatibility. Disabling NVLS via the NCCL_NVLS_ENABLE environment variable forces NCCL to use standard algorithms, which are robust and should eliminate the errors. Other options either do not target NVLS or are less direct and potentially disruptive.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the NCCL buffer size by setting NCCL_BUFFSIZE to a larger value to reduce the number of messages.
Why it's wrong here
Increasing buffer size can improve performance in some cases, but it does not address NVLS errors. NVLS errors indicate a problem with the SHARP acceleration, not buffer capacity. Changing buffer size may even exacerbate memory pressure. This action does not resolve the underlying incompatibility or failure of NVLS, so the errors would persist.
- ✓
Disable NVLink SHARP by setting NCCL_NVLS_ENABLE=0 in the environment and restart the job.
Why this is correct
NVLS (NVLink SHARP) is an in-network reduction feature that can accelerate all-reduce operations, but it requires compatible hardware and software. If errors occur, disabling it forces NCCL to fall back to standard ring or tree algorithms, which are reliable. This resolves the immediate errors and restores communication performance, though it may not achieve peak efficiency. It is a valid troubleshooting step when NVLS is unstable.
- ✗
Update the GPU driver and CUDA toolkit to the latest versions to fix NVLS bugs.
Why it's wrong here
Updating drivers and CUDA may resolve some issues, but it is not a guaranteed fix and may introduce other compatibility problems. The immediate errors require a configuration change to disable the failing feature. In a production environment, updating software without testing can be risky. This action does not directly address the NVLS errors and may delay resolution.
- ✗
Switch the NCCL algorithm to 'Tree' by setting NCCL_ALGO=Tree to avoid NVLS usage.
Why it's wrong here
While setting NCCL_ALGO=Tree can bypass NVLS, it is not the recommended first step because it forces a specific algorithm that may not be optimal for all topologies. The direct way to disable NVLS is via NCCL_NVLS_ENABLE=0. Additionally, Tree algorithm might not be supported for all collective types. This option is less precise and could lead to suboptimal performance.
Visual reference
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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.