Individual skill

fragmentation-aware-packing

Choose placements that preserve useful residual capacity. Use for bin packing, GPU sharing, accelerator placement, and multi-resource scheduling where stranded capacity hurts future fit.

tasks-extra/gpu-cluster-online-scheduling/environment/skills/fragmentation-aware-packing/SKILL.md

Read pinned source

Source commit f860ecf02ef53412a030f8661c83d644b739ff01

What was checked

Matches the observed repository HEAD: Yes
Scanner rules are current: Yes
Repository scan complete: No
Skill scan complete: Yes
Observed behavior: Instructions only
Last checked: Nov 9, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings): 1,910
Repository last updated: Nov 4, 2026
License: Apache-2.0

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

benchmark Repository topic
skillsbench Repository topic
engineering Derived category

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files

SKILL.mdcore · 3,929 bytes

Read excerpt


# Fragmentation-Aware Packing

Use this skill when several feasible placements exist and the choice affects future capacity.

## Core Idea

A placement is not good just because it fits. Good placements preserve useful residual capacity. With fractional GPUs, this often means packing small compatible jobs together while preserving whole or scarce GPU slots. The same idea applies to any slots, bins, or resources with discrete capacities.

## Marginal Fragmentation

For each feasible placement, compute a local before/after estimate:

1. Measure current free capacity by resource type and slot.
2. Copy the target machine or bin state.