simd

l is a new runtime for k4, q, and qSQL that provides transparent SIMD, compressed vectors, and automatic parallelism while maintaining full compatibility with existing code. It targets high-performance computing on Wall Street.

A developer details the process of optimizing a Go file search from 0.75 GB/s to 49 GB/s, leveraging techniques like SIMD and understanding memory hierarchy, including Go 1.26's new `simd/archsimd` package.

After a year of research, a universal 2x performance improvement for all modern JavaScript parsers is being implemented, starting with oxc_parser, which will speed up tools like OXLint, Vite, and Deno, and potentially major browser engines.

CParseC is a single-header C99 library for parser combinators inspired by Haskell's Parsec, offering zero-copy parsing, no hidden allocations, and SIMD-optimized combinators. It aims to provide a flexible, performant alternative to handwritten parsers and lex/yacc tools.

A blog post describing a tiny compiler that demonstrates how to lower data-parallel kernels by converting for loops into vectorized loops with lanes and masks, implemented in ~180 lines of Python.

The paper presents simdjson, the first validating JSON parser capable of processing gigabytes per second on a single core using SIMD instructions, achieving substantial speedups over existing parsers like RapidJSON.

Rust's SIMD abstractions now allow safe usage without unsafe code by leveraging CPU feature tokens introduced in Rust 1.87, enabling concise and portable vector operations.

Modular demonstrates two approaches for computing game fields: using SIMD precomputation or compiling a Mojo kernel to WebAssembly for live browser rendering.

A Mojo program uses 8 SIMD lanes to generate game levels based on GPU thermal fields, with heat creating obstacles and coolant adding boosts.

This article details how Clojure, with the JVM's Vector API and careful optimization, achieved frame rates within 20% of C for a 3D stress test, demonstrating that a dynamic language can approach low-level performance on hot loops.

This paper presents PivCo-Huffman, a new approach to Huffman coding using pivot coding from wavelet trees, enabling high-performance SIMD-friendly encoding and decoding. It consistently outperforms state-of-the-art Huffman codecs and shows how ANS coding can be selectively applied to skewed nodes to approach ANS compression ratios while preserving high decompression speeds.

Blog post analyzing and implementing a SIMD-accelerated version of std::copy_if using AVX-512 instructions on AMD Zen 4, with performance analysis and comparisons to compiler auto-vectorization.

An in-depth technical blog post explaining how to efficiently transpose matrices using SIMD instructions on modern x86_64 CPUs, focusing on AVX2 intrinsics like _mm256_shuffle_epi8.

Bun.Image is a zero-dependency chainable image pipeline for decoding, resizing, rotating, and re-encoding JPEG, PNG, WebP, HEIC, and AVIF, running off-thread and inspired by Sharp.

minc is a minimal programming language that compiles directly to native executables for multiple platforms without external tooling. It features modern syntax, built-in SIMD, and a bundled shader compiler.

The article criticizes the new std::simd library in C++26, arguing it is slower than scalar loops, compiles slowly, and is outperformed by auto-vectorizers and alternative libraries like Google Highway, questioning its value after a decade-long standardization process.

turbovec is an open-source Rust vector index using Google Research's TurboQuant algorithm, achieving 16x compression and faster search than FAISS, with integrations for RAG frameworks like LangChain, LlamaIndex, and Haystack.

The author details the third iteration of the bx library's cross-platform SIMD abstraction, advocating for a typeless approach and SSA-style coding to simplify low-level performance optimization across different CPU architectures.

planb-lpm is a portable, MIT-licensed C++17 library implementing efficient IPv6 longest-prefix-match (LPM) using a linearized B+-tree with AVX-512 SIMD, featuring dynamic FIB support, Python bindings, and comprehensive benchmarking against real BGP data.

This article explores the fastest methods for matching characters on ARM processors using SIMD instructions, comparing traditional NEON approaches with newer SVE2 capabilities available on modern ARM chips like AWS Graviton4, Google Axion, and others.