palmetto-slurm-fit-check

Evaluate SBATCH resource requests against Palmetto node availability.

Updated Apr 10, 2026
One-click install
npx skills add https://github.com/KwongFuk/codex-skills --skill palmetto-slurm-fit-check
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: palmetto-slurm-fit-check
Source: https://github.com/KwongFuk/codex-skills/tree/main/global/palmetto-slurm-fit-check
Command: npx skills add https://github.com/KwongFuk/codex-skills --skill palmetto-slurm-fit-check

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Palmetto Slurm Fit Check helps HPC users determine if a requested CPU/GPU/memory configuration can start on Palmetto now, reducing wasted submission attempts and improving cluster utilization.

Core Features & Use Cases

  • Read and interpret SBATCH directives or explicit resource requests.
  • Evaluate per-node availability, GPU counts, CPU fragmentation, and memory to provide actionable verdicts.
  • Use cases include validating sbatch submissions, tuning cpus-per-task, and deciding whether to wait or reduce resources.

Quick Start

Evaluate a SBATCH script or a direct resource request to determine whether the job can start now, requires CPU reduction, or should wait.

Frequently Asked Questions about palmetto-slurm-fit-check

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check if my Palmetto Slurm job request will fit available nodes?

Check whether your Palmetto Slurm job fits available nodes by parsing SBATCH directives for CPU, GPU, and memory requests against per-node availability, yielding heuristic verdicts like CAN_RUN_NOW or WAIT_FOR_GPUS to guide submission.

What does it mean when a Slurm GPU job submission requires reducing CPUs?

When a Slurm GPU job submission requires reducing CPUs, it means per-node CPU fragmentation prevents the job from starting now, prompting a LOWER_CPU_AND_RESUBMIT verdict to tune your cpus-per-task and improve cluster utilization.

Can I validate an sbatch script for Palmetto cluster GPU availability before submitting?

Yes, you can validate an sbatch script for Palmetto cluster GPU availability by reading and interpreting SBATCH directives to evaluate GPU counts and memory constraints before actually submitting the job.

Why is my Palmetto HPC job stuck waiting when requesting specific GPU resources?

Your Palmetto HPC job is stuck waiting because the requested GPU resources exceed current per-node availability, resulting in a WAIT_FOR_GPUS verdict indicating you should wait or adjust your resource allocation.

What is the best way to optimize resource allocation for Palmetto sbatch submissions?

The best way to optimize resource allocation for Palmetto sbatch submissions is evaluating CPU, GPU, and memory tradeoffs against cluster fragmentation to determine whether to run now, lower resources, or wait.