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Enhanced Slurm Cluster Monitoring with GPUd and Lepton AI #2

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Summary

This document details how to integrate GPUd for real-time GPU monitoring and Lepton AI for centralized dashboarding into a Slurm cluster deployed on Crusoe Cloud. This enhances cluster observability and allows for proactive issue detection.

Motivation

These changes are necessary to provide users with a comprehensive solution for monitoring GPU health and performance within their Slurm clusters. By integrating GPUd and Lepton AI, users can:

  • Proactively identify issues: Detect hardware and system-level problems early, reducing downtime.
  • Centralized monitoring: View GPU metrics across the entire cluster in a single dashboard.
  • Improve resource utilization: Gain insights into GPU usage patterns to optimize job scheduling.
  • Simplify management: Streamline the process of monitoring and maintaining GPU resources.

For new content

  • I have added a new entry in registry.yaml (and, optionally, in authors.yaml) so that my content renders on the cookbook website.
  • I have conducted a self-review of my content based on the contribution guidelines:
    • Relevance: This content is directly related to building and managing Slurm clusters on Crusoe Cloud, a core use case.
    • Uniqueness: This guide provides a specific integration of GPUd and Lepton AI, which is not covered in existing documentation.
    • Spelling and Grammar: I have carefully reviewed the text for errors.
    • Clarity: The instructions are step-by-step and easy to follow.
    • Correctness: The commands and configurations have been tested and are accurate.
    • Completeness: The guide covers all necessary steps, from initial setup to accessing the dashboards.

@MichaelMcCulloch-deepsense-ai MichaelMcCulloch-deepsense-ai marked this pull request as ready for review December 18, 2024 13:04
@MichaelMcCulloch-deepsense-ai
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MichaelMcCulloch-deepsense-ai commented Dec 18, 2024

Would you prefer this logic to be encapsulated in the terraform module for slurm? @ethxnp. My feeling is that keeping it within cookbook paints a cohesive picture of what is going on, with rather little overhead.

On the other hand, encapsulating it in the module for slurm hides complexity at the expense of understanding, and I feel doing so would diminish understanding more than it would diminish complexity.

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