simd

DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps

Acceleration package for neural networks on multi-core CPUs

Gluten is a middle layer responsible for offloading JVM-based SQL engines' execution to native engines.

Optimized string search routines for Rust.

SIMD Vector Classes for C++

A translator from Intel SSE intrinsics to Arm/Aarch64 NEON implementation

World's Fastest .NET CSV Parser. Modern, minimal, fast, zero allocation, reading and writing of separated values (`csv`, `tsv` etc.). Cross-platform, trimmable and AOT/NativeAOT compatible with blazing fast SIMD vectorized parsing.

fastest text uwuifier in the west

Rust port of simdjson

Modular node graph based noise generation library using SIMD, C++17 and templates

Expressive Vector Engine - SIMD in C++ Goes Brrrr

Web Serving and Remote Procedure Calls at 50x lower latency and 70x higher bandwidth than FastAPI, implementing JSON-RPC & REST over io_uring ☎️

Portable header-only C++ low level SIMD library

Jlama is a modern LLM inference engine for Java

A linear algebra and mathematics library for computer graphics.

Math library using HLSL syntax with multiplatform SIMD support

Unsafely fast hashing algorithm 📈

Library for specialized dense and sparse matrix operations, and deep learning primitives.

Go library providing algorithms optimized to leverage the characteristics of modern CPUs

Zero-copy PDF text extraction library written in Zig. High-performance, memory-mapped parsing with SIMD acceleration.

A fast Rust JSON library based on SIMD.

High performance LINQ implementation with minimal heap allocations. Supports enumerables, async enumerables, arrays and Span<T>.

SIMD Library for Evaluating Elementary Functions, vectorized libm and DFT

A lightweight high performance tensor algebra framework for modern C++

Fastest Integer Compression

Llama 3+ inference in pure Java

Realtime Math

Macro(s) for vectorizing loops.

Python bindings for the simdjson project.

Linq-like extension functions for Arrays, Span<T>, and List<T> that are faster and allocate less.