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highway

brew install highway v1.4.0 Apache-2.0 OR BSD-3-Clause

C++ header-only SIMD library providing portable vector intrinsics with runtime CPU dispatch across x86, ARM, WebAssembly, and other architectures.

Why you might care

Highway lets you write performance-critical code once and automatically dispatch to the fastest available CPU instructions (SSE4.2, AVX, AVX-512, NEON, etc.) at runtime. Unlike hand-rolled intrinsics or compiler autovectorization, it's predictable, maintainable, and works reliably across platforms. Essential for numeric libraries, video codecs, and data-parallel workloads that need 5–10x speedups with lower energy use.

Categories

Alternatives

Boost.SIMD Vc Eve Intel IPP
19.9k
30-day installs · #236
94.3k
90-day · #188
564.8k
365-day · #128
5.6k
★ GitHub stars · updated today

Build dependencies

GitHub topics

avx avx-512 avx-instructions avx2 avx512 intrinsics neon simd simd-instructions simd-intrinsics simd-library simd-parallelism simd-programming sse42 wasm

Links

Blurb generated by claude-haiku-4-5 on today.

Raw metadata
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  "desc": "Performance-portable, length-agnostic SIMD with runtime dispatch",
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  "github_last_commit_at": "2026-06-20T15:49:40Z",
  "github_readme_excerpt": "# Efficient and performance-portable vector software\n\n[//]: # (placeholder, do not remove)\n\nHighway is a C++ library that provides portable SIMD/vector intrinsics.\n\n[Documentation](https://google.github.io/highway/en/master/)\n\nPreviously licensed under Apache 2, now dual-licensed as Apache 2 / BSD-3.\n\n## Why\n\nWe are passionate about high-performance software. We see major untapped\npotential in CPUs (servers, mobile, desktops). Highway is for engineers who want\nto reliably and economically push the boundaries of what is possible in\nsoftware.\n\n## How\n\nCPUs provide SIMD/vector instructions that apply the same operation to multiple\ndata items. This can reduce energy usage e.g. *fivefold* because fewer\ninstructions are executed. We also often see *5-10x* speedups.\n\nHighway makes SIMD/vector programming practical and workable according to these\nguiding principles:\n\n**Does what you expect**: Highway is a C++ library with carefully-chosen\nfunctions that map well to CPU instructions without extensive compiler\ntransformations. The resulting code is more predictable and robust to code\nchanges/compiler updates than autovectorization.\n\n**Works on widely-used platforms**: Highway supports seven architectures; the\nsame application code can target various instruction sets, including those with\n\u0027scalable\u0027 vectors (size unknown at compile time). Highway only requires C++17\n(language features, not necessarily the library) and supports four families of\ncompilers. If you want to use Highway on other platforms, please raise an issue.\n\n**Flexible to deploy**: Applications using Highway can run on heterogeneous\nclouds or client devices, choosing the best available instruction set at\nruntime. Alternatively, developers may choose to target a single instruction set\nwithout any runtime overhead. In both cases, the application code is the same\nexcept for swapping `HWY_STATIC_DISPATCH` with `HWY_DYNAMIC_DISPATCH` plus one\nline of code. See also @kfjahnke\u0027s\n[introduction to dispatching](https://g",
  "github_repo": "google/highway",
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  "homepage": "https://github.com/google/highway",
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  "installs_30d": 19853,
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  "installs_90d": 94284,
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  "last_seen": "2026-06-20T23:34:18+00:00",
  "license": "Apache-2.0 OR BSD-3-Clause",
  "llm_generated_at": "2026-06-20T23:43:37+00:00",
  "llm_model": "claude-haiku-4-5",
  "name": "highway",
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  "one_liner": "C++ header-only SIMD library providing portable vector intrinsics with runtime CPU dispatch across x86, ARM, WebAssembly, and other architectures.",
  "optional_dependencies": [],
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  "raw_hash": "8d4ee18e3c485a1c",
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  "ruby_source_path": "Formula/h/highway.rb",
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  "version_head": "HEAD",
  "version_stable": "1.4.0",
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  "why_use_this": "Highway lets you write performance-critical code once and automatically dispatch to the fastest available CPU instructions (SSE4.2, AVX, AVX-512, NEON, etc.) at runtime. Unlike hand-rolled intrinsics or compiler autovectorization, it\u0027s predictable, maintainable, and works reliably across platforms. Essential for numeric libraries, video codecs, and data-parallel workloads that need 5\u201310x speedups with lower energy use."
}