NCA-AIIO Question 104
Select 3A company is deploying an AI cluster to train complex deep learning models. They need to ensure optimal resource utilization and efficient job scheduling across multiple GPUs within the cluster. Which of the following features are essential for their AI cluster orchestration and job scheduling solution?
- A
Support for workload prioritization and preemption
- B
Static GPU allocation to specific jobs without dynamic reallocation
- C
Integration with container orchestration platforms like Kubernetes
- D
Fine-grained resource management, such as GPU memory and compute partitioning
- E
Manual intervention for job scheduling and resource allocation
Show answer and explanation
Correct answers: A, C, D
Explanation
Effective AI cluster orchestration and job scheduling solutions should support features like workload prioritization, integration with orchestration platforms, and fine-grained resource management to ensure optimal resource utilization and scalability. Static GPU allocation and manual intervention do not align with the goals of modern, efficient AI infrastructure.
- A. Correct.
Workload prioritization and preemption are critical to ensure high-priority jobs are executed on time, especially in shared AI infrastructure environments.
- B. Incorrect.
Static GPU allocation without dynamic reallocation can lead to inefficient resource utilization and idle GPUs, making it unsuitable for modern AI workloads.
- C. Correct.
Integration with container orchestration platforms like Kubernetes allows for automated and scalable management of AI workloads, which is essential for efficient operations.
- D. Correct.
Fine-grained resource management enables better utilization of GPU resources by allowing multiple jobs to share GPUs effectively, increasing cluster efficiency.
- E. Incorrect.
Manual intervention for job scheduling and resource allocation is inefficient and error-prone, making it a non-essential feature for modern AI cluster orchestration.