In an AI cluster, what is the purpose of job scheduling?

The correct answer is C. To assign workloads to available compute resources. A job scheduler (e.g., SLURM, Kubernetes with GPU support, or NVIDIA Base Command) is responsible for queuing, prioritizing, and dispatching AI training or inference jobs to the appropriate compute nodes and GPUs within a cluster. It ensures resources are utilized efficiently…

NVIDIA Infrastructure and Operations

Question

Options

ATo gather and analyze cluster data on a regular schedule.
BTo monitor and troubleshoot cluster performance.
CTo assign workloads to available compute resources.
DTo install, update, and configure cluster software.

How the community answered

(59 responses)

A
7% (4)
B
3% (2)
C
88% (52)
D
2% (1)

Explanation

A job scheduler (e.g., SLURM, Kubernetes with GPU support, or NVIDIA Base Command) is responsible for queuing, prioritizing, and dispatching AI training or inference jobs to the appropriate compute nodes and GPUs within a cluster. It ensures resources are utilized efficiently, prevents conflicts, and enforces priorities or quotas. Option A describes data collection/analytics, not scheduling. Option B describes monitoring tools (e.g., DCGM, Prometheus). Option D describes configuration management or orchestration tools (e.g., Ansible, Helm). None of these are the primary role of a job scheduler.

Topics

#Job scheduling#Resource allocation#AI cluster management

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