# vectorclass/version2

Vector class library, latest version

Repository: https://github.com/vectorclass/version2
Canonical: https://ross.abutalabs.com/products/version2
Language: C++
License: Apache-2.0
License Family: permissive
Last push: 2026-04-14T06:22:55+00:00

## Health v2 (maintenance only)
Score: 71/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 77, release rhythm 47, longevity 100
- inputs: {"age_days": 2589, "days_push": 141, "days_rel": 141, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1474, forks 155 (observed 2026-08-28T04:04:49.678655+00:00)

## What it is
A C++ class library for using SIMD instructions (SSE, AVX, AVX-512) to improve performance on x86/x86-64 microprocessors. It provides vector classes that abstract over platform-specific intrinsics across Windows, Linux, and Mac.

## Use cases
- vectorize numeric loops with SIMD without writing intrinsics
- write portable SIMD code across SSE, AVX2, and AVX-512
- accelerate image or signal processing kernels on x86
- speed up math-heavy scientific computing code
- abstract CPU vector widths in C++ with a single API

## When to choose
- you need SIMD performance on x86/x86-64 without hand-writing intrinsics
- you want one codebase targeting multiple SIMD instruction sets
- you are doing numerical, media, or scientific computing in C++

## When to avoid
- you target ARM, NEON, or other non-x86 instruction sets
- you need GPU or multi-core parallelism rather than single-core SIMD
- your project is not C++

## Facets
- artifact type: library
- maturity: stable
- function: math, graphics, simulation
- domain: performance, developer-tools
- platform: cpp, windows, cross-platform
- tags: simd, vectorization, x86, avx, sse, numerical-computing, algorithms, linux, macos

## Member repositories
- vectorclass/version2 (main) score 71

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:49.678655+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 2026-08-30T04:34:34.942073+00:00, confidence not recorded.
  - readme: https://github.com/vectorclass/version2 (fetched 2026-08-28T04:04:49.678655+00:00, sha 4345c083cfae)
- Data as of 2026-08-30T08:39:29.467469+00:00.