Sign in

Repository Index

47,133 repositories indexed

Filters

Filters

Clear all filters

1–22 of 22 · Most stars

SeaweedFS is a distributed storage system for object storage (S3), file systems, Iceberg table buckets, and Lance vector buckets, designed to handle billions of files with O(1) disk access and effortless horizontal scaling.

The world's fastest open query engine for sub-second analytics both on and off the data lakehouse. With the flexibility to support nearly any scenario, StarRocks provides best-in-class performance for multi-dimensional analytics, real-time analytics, and ad-hoc queries. A Linux Foundation project.

🗺 MapSCII is a Braille & ASCII world map renderer for your console - enter => telnet mapscii.me <= on Mac (brew install telnet) and Linux, connect with PuTTY on Windows

  • ascii-art
  • map
  • vector-tiles
  • braille

Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍

Implementations of SIMD instruction sets for systems which don't natively support them.

  • simd-intrinsics
  • sse
  • neon
  • arm

Unicode routines (UTF8, UTF16, UTF32) and Base64: billions of characters per second using SSE2, AVX2, NEON, AVX-512, RISC-V Vector Extension, LoongArch64, POWER. Part of Node.js, WebKit/Safari, Ladybird, Chromium, Cloudflare Workers, Ghostty and Bun.

  • utf8
  • utf16
  • unicode
  • simd

SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go 📐

One of the World's Fastest .NET CSV Parsers. 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.

  • csharp
  • csv
  • csv-parser
  • csv-reader

GRASS - free and open-source geospatial processing engine

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

Example of implementing Support Vector Machine (SVM) with RBF (Gaussian) kernel in Ruby using rb-libsvm. .

  • rubyml
  • ruby
  • svm
  • svm-classifier