# AccelerateHS/accelerate

Embedded language for high-performance array computations

Repository: https://github.com/AccelerateHS/accelerate
Canonical: https://ross.abutalabs.com/products/acceleratehs-accelerate
Homepage: https://www.acceleratehs.org
Language: Haskell
License: NOASSERTION
License Family: other
Topics: haskell, accelerate, llvm, cuda, parallel-computing, gpu-computing, gpu, hacktoberfest
Last push: 2026-06-20T14:14:22+00:00

## Health v2 (maintenance only)
Score: 62/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 88, release rhythm 8, longevity 100
- inputs: {"age_days": 5626, "days_push": 74, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1018, forks 135 (observed 2026-08-28T04:03:14.881990+00:00)

## What it is
Accelerate is an embedded domain-specific language in Haskell for high-performance, multi-dimensional array computations. Programs written as collective operations are online-compiled via LLVM or CUDA backends to run on multicore CPUs and GPUs.

## Use cases
- run array computations on GPUs from Haskell
- write high-performance parallel numeric code
- accelerate compute-intensive kernels like dot products or stencil operations
- compile Haskell array programs to LLVM or CUDA
- prototype GPGPU programs in a high-level functional style
- offload dense linear algebra or image processing workloads

## When to choose
- you program in Haskell and need GPU or multicore acceleration for dense array math
- you want type-safe, declarative parallel code without writing CUDA by hand
- you need portable performance across CPU and GPU backends

## When to avoid
- you need irregular or sparse data structures rather than dense regular arrays
- your project is not in Haskell
- you need fine-grained manual control over GPU kernels or memory layout
- you need a mature ecosystem of ML libraries on GPU

## Facets
- artifact type: library
- maturity: active
- function: compiler, gpu-computing, math, concurrency
- domain: gpu-computing, programming-languages, compilers, performance
- platform: cpp, cross-platform
- tags: embedded-language, array-computing, llvm, cuda, parallel-computing, haskell, gpgpu, high-performance-computing, algorithms, gpu

## Member repositories
- AccelerateHS/accelerate (main) score 62

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:14.881990+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 2026-08-30T07:09:25.360068+00:00, confidence not recorded.
  - readme: https://github.com/AccelerateHS/accelerate (fetched 2026-08-28T04:03:14.881990+00:00, sha f9279ae8c8e1)
  - homepage: https://www.acceleratehs.org (fetched 2026-08-29T13:09:35.590561+00:00, sha 13c27b621e17)
  - site_page: https://www.acceleratehs.org/documentation.html (fetched 2026-08-29T13:09:35.593020+00:00, sha fbbefa9fde0b)
- Data as of 2026-08-30T08:39:29.467469+00:00.