# uncomplicate/neanderthal

Fast Clojure Matrix Library

Repository: https://github.com/uncomplicate/neanderthal
Canonical: https://ross.abutalabs.com/products/neanderthal
Homepage: http://neanderthal.uncomplicate.org
Language: Clojure
License: EPL-1.0
License Family: copyleft
Topics: clojure, clojure-library, matrix, gpu, gpu-computing, gpgpu, opencl, cuda, high-performance-computing, vectorization, api, matrix-factorization, matrix-multiplication, matrix-functions, matrix-calculations, java
Last push: 2026-08-19T15:51:37+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 35, longevity 100
- inputs: {"age_days": 4402, "days_push": 14, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1128, forks 61 (observed 2026-08-28T04:03:41.977463+00:00)

## What it is
Neanderthal is a fast Clojure library for matrix and linear algebra computations built on optimized native BLAS and LAPACK routines, supporting both CPU and GPU (CUDA, OpenCL) engines. It offers a Clojure-idiomatic API with pluggable engines, including a pure Java fallback.

## Use cases
- fast matrix multiplication in Clojure
- GPU-accelerated linear algebra on the JVM
- solve linear systems with LAPACK from Clojure
- matrix factorization and decompositions
- high-performance numerical computing in Clojure
- vectorized math operations on large vectors and matrices

## When to choose
- you need native-speed BLAS/LAPACK performance from Clojure
- you want to run linear algebra on AMD, Nvidia, or Intel GPUs
- pure Java math libraries are too slow for your workload
- you want a Clojure-idiomatic API over decades-standardized BLAS/LAPACK routines

## When to avoid
- you need a pure-Java, dependency-free solution
- your project is not on the JVM/Clojure
- you only need simple, small-scale matrix math where native bindings add complexity

## Facets
- artifact type: library
- maturity: active
- function: math, gpu-computing
- domain: machine-learning, data-science, performance
- platform: jvm, jvm-scripting, windows
- tags: linear-algebra, blas, lapack, matrix, opencl, cuda, clojure, high-performance-computing, algorithms, linux, macos, gpu

## Member repositories
- uncomplicate/neanderthal (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:41.977463+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 2026-08-30T06:38:44.602766+00:00, confidence not recorded.
  - readme: https://github.com/uncomplicate/neanderthal (fetched 2026-08-28T04:03:41.977463+00:00, sha 01d198ffb85f)
  - homepage: http://neanderthal.uncomplicate.org (fetched 2026-08-29T12:43:09.606422+00:00, sha 1b2834dc45d3)
  - site_page: https://neanderthal.uncomplicate.org/codox (fetched 2026-08-29T12:43:09.608951+00:00, sha a3e5f23beac0)
- Data as of 2026-08-30T08:39:29.467469+00:00.