# KarypisLab/METIS

METIS - Serial Graph Partitioning and Fill-reducing Matrix Ordering

Repository: https://github.com/KarypisLab/METIS
Canonical: https://ross.abutalabs.com/products/karypislab-metis
Language: C
License: NOASSERTION
License Family: other
Topics: graph, partitioning-algorithms
Last push: 2026-06-10T21:37:25+00:00

## Health v2 (maintenance only)
Score: 71/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 86, release rhythm 35, longevity 100
- inputs: {"age_days": 2375, "days_push": 84, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1049, forks 212 (observed 2026-08-28T04:03:22.768012+00:00)

## What it is
METIS is a C library and set of serial programs for partitioning graphs and finite element meshes, and for computing fill-reducing orderings of sparse matrices. It implements multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning algorithms.

## Use cases
- partition a large graph into balanced parts
- compute fill-reducing orderings for sparse matrix factorization
- partition finite element meshes for parallel simulation
- split graphs for distributed computing workloads
- multi-constraint graph partitioning for load balancing

## When to choose
- you need fast, high-quality graph or mesh partitioning in C/C++
- you want fill-reducing orderings for sparse linear solvers
- you need a mature, widely used HPC partitioning library

## When to avoid
- you need distributed (multi-node) partitioning rather than serial
- you need a pure Python or managed-language solution
- you require a permissively simple license without checking the Apache 2.0 terms

## Facets
- artifact type: library
- maturity: stable
- function: math, simulation, developer-tools
- domain: mathematics, simulation, performance
- platform: windows, cpp, c
- tags: graph-partitioning, sparse-matrix, fill-reducing-ordering, finite-element-mesh, hpc, scientific-computing, algorithms, linux, macos

## Member repositories
- KarypisLab/METIS (main) score 71

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:22.768012+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:00:27.181470+00:00, confidence not recorded.
  - readme: https://github.com/KarypisLab/METIS (fetched 2026-08-28T04:03:22.768012+00:00, sha 200c9002ff62)
- Data as of 2026-08-30T08:39:29.467469+00:00.