Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
A vector index built on TurboQuant, written in Rust with Python bindings
A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.
Chromium fork named after radioactive element No. 90. Source code and Linux releases. Windows/MacOS/ARM builds served in different repos, links are towards the top of the README.md.
Performance-portable, length-agnostic SIMD with runtime dispatch
Fast inference engine for Transformer models
Open-source library of optimized deep learning operations (matmul, convolution, attention) for CPUs (x64, AArch64, RISC-V) and Intel GPUs. Used by PyTorch, TensorFlow, OpenVINO, and ONNX Runtime.
Up to 100x faster strings for C, C++, CUDA, Python, Rust, Swift, JS, & Go, leveraging NEON, AVX2, AVX-512, SVE, GPGPU, & SWAR to accelerate search, hashing, sorting, edit distances, sketches, and memory ops 🦖
Implementations of SIMD instruction sets for systems which don't natively support them.
Open-source, self-hosted customer support desk in a single binary. A lightweight alternative to Intercom, Zendesk, Chatwoot.
DAVx⁵ is an open-source CalDAV/CardDAV suite and sync app for Android. You can also access your online files (WebDAV) with it.
C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, AVX512, NEON, SVE, WebAssembly, VSX, RISC-V))
Chromium fork for Windows named after radioactive element No. 90; Windows builds of https://github.com/Alex313031/Thorium
A JIT assembler for x86/x64 architectures supporting the latest instruction set extensions such as AVX10.2 and ACE
C++ image processing and machine learning library with using of SIMD: SSE, AVX, AVX-512, AMX for x86/x64, NEON, SVE for ARM, HVX for Hexagon
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.
Fast, modern C++ DSP framework, FFT, Sample Rate Conversion, FIR/IIR/Biquad Filters (SSE, AVX, AVX-512, ARM NEON, RISC-V RVV)
Roaring bitmaps in C (and C++), with SIMD (AVX2, AVX-512 and NEON) optimizations: used by Apache Doris, ClickHouse, Alibaba Tair, Redpanda, YDB and StarRocks
DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps
Expressive Vector Engine - SIMD in C++ Goes Brrrr
Math library using HLSL syntax with multiplatform SIMD support
🚀 Fast prime number generator
C++ template library for high performance SIMD based sorting algorithms
Library for specialized dense and sparse matrix operations, and deep learning primitives.
Fastest Integer Compression
jtx Board allows you to manage your Journals (like meeting minutes), Notes and Tasks in one Android app. The app is compatible with the iCal standard (RFC5545) and is integrated with DAVx5 to allow the synchronisation of entries through CalDAV.
Portable wrapper for SIMD and vector instructions written in C++11. Compatible with NEON, SSE, AVX, AVX-512 and SVE (length specific).
37 tok/s from Qwen3-Next-80B (48 GB) on a 32 GB laptop, 24 without drafts vs 2.8 for llama.cpp; reading 62 vs 16 tok/s. Faster than llama.cpp on all 13 models compared in Q4_K_M. LLMs bigger than your RAM, pure C, CPU or GPU.
GLM-5.3-Flash EXL3 on one 24 GB RTX 3090 + DDR4: elastic GPU expert cache, zero-copy experts, AVX2 CPU tier, OpenAI API
Strata fork: Qwen3.8-Flash-Next 125B MoE in NVFP4 on one RTX 20-50 card (12 GB+) and 64 GB of RAM or more. Setup installs our GPTQ quants (huihui abliterated, OrcaRouter) from Hugging Face. CPU experts on AVX-512 or AVX2 (+AVX-VNNI), all experts in RAM from 92 GB, a low-RAM mode below, vision, W4A8 prompts. Windows / CUDA 13.
DeepSeek-V4.1-Flash EXL3 on one 24 GB RTX 3090 + DDR4 + NVMe: staged-DMA prefill, AVX2 CPU expert tier, elastic VRAM expert cache, Engram on disk, OpenAI API
exact tokenizers ids, as fast as the hardware allows
A tiny neural-network framework in pure Go with AVX2 SIMD kernels (GOEXPERIMENT=simd)
Wire v9: from-scratch ultra-low-latency HFT stack in Rust and C. 24 crates: TCP/IP, AF_XDP, VFIO PCIe DMA, LMAX Disruptor, AVX2/AVX-512 SIMD, flat-array matching engine (11 cyc), HugePage slab (1.5 ns), lock-free MPMC, CME MDP 3.0 SBE, eBPF XDP risk. Zero heap allocs on the hot path. 46/46 tests pass.
Расписание ИТМО в календаре: ICS-подписка и read-only CalDAV для Apple Календаря, Google Календаря, Thunderbird, DAVx⁵, Outlook, Nextcloud и Android.
Forensic reverse-engineering, hardware benchmarks, and architectural security analysis of JioPC Cloud Virtual Desktops (Accops HyWorks / Azure).
a pure C# implementation of GCDRNet (Appearance Enhancement for Camera-captured Document Images in the Wild, IEEE TAI 2023) — document-image shadow removal and appearance enhancement without onnxruntime or any other third-party inference engine. It ships its own compiled-model inference engine
Pure C implementation of FastEnhancer. 3.3x faster than the ONNX Runtime graph, same quality.