NCA-AIIO Question 101
Select 3An organization is using a GPU-powered AI cluster to run multiple AI training jobs. The cluster uses a job scheduler for resource allocation and workload management. Which of the following are key benefits of using a job scheduler in this environment?
- A
Efficient allocation of GPU resources across multiple jobs
- B
Automatic scaling of hardware resources beyond the physical cluster
- C
Fair sharing of resources among users or teams based on defined policies
- D
Improved training model accuracy through optimized GPU kernel execution
- E
Simplified management of job priorities and dependencies between workloads
Show answer and explanation
Correct answers: A, C, E
Explanation
Job schedulers play a critical role in AI cluster orchestration by managing resource allocation, enforcing fair usage policies, and simplifying the execution of complex workflows with dependent jobs. This ensures efficient utilization of GPU resources and improves operational efficiency in multi-user, multi-job environments.
- A. Correct.
Efficient allocation of GPU resources is a core function of job schedulers, ensuring optimal cluster utilization and preventing resource contention.
- B. Incorrect.
Automatic scaling of hardware resources beyond the physical cluster is not a direct feature of job schedulers. This requires integration with cloud-based or hybrid infrastructure solutions.
- C. Correct.
Fair sharing of resources is a key benefit of job schedulers, enabling multi-user environments to enforce policies and avoid resource monopolization.
- D. Incorrect.
Improved training model accuracy is unrelated to job scheduling or orchestration. Accuracy depends on factors like model design, data quality, and hyperparameters.
- E. Correct.
Job schedulers simplify the management of job priorities and dependencies by allowing users to define task order and precedence, ensuring efficient workflow execution.