32 个仓库
High-speed mathematical operations performed on entire data series.
Distinguishing note: Focuses on broadcasting and series-level arithmetic.
Explore 32 awesome GitHub repositories matching data & databases · Vectorized Arithmetic. Refine with filters or upvote what's useful.
Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e
Executes arithmetic operations between series with automatic broadcasting and missing value handling.
AISystem is a comprehensive AI full-stack infrastructure project covering the entire pipeline from AI chip architecture to high-level training frameworks. It encompasses the development of AI compiler frameworks, inference engines, and distributed training orchestrators designed to coordinate workloads across a heterogeneous compute stack of CPUs, GPUs, and NPUs. The project focuses on the deep integration of software and hardware, employing software-hardware co-design to align tensor layouts with physical memory structures. It provides specialized capabilities for accelerating Transformer mo
Applies a single instruction across multiple data elements simultaneously to accelerate vector operations.
GGML is a machine learning tensor library and neural network engine written in C. It functions as a compute-focused runtime designed to execute transformer-based models and perform complex mathematical operations on multi-dimensional arrays directly on local consumer hardware. The library distinguishes itself by enabling local inference for large language models and edge machine learning deployment without reliance on external cloud infrastructure. It achieves this through a tensor-based computation graph that organizes operations for efficient execution and memory management, alongside stati
Utilizes processor-specific instruction sets to perform parallel arithmetic operations on data arrays for significantly faster mathematical throughput.
John is a command-line security utility designed for password strength auditing and cryptographic hash recovery. It functions as a professional tool for identifying weak user credentials and recovering access to protected files, archives, and private keys across various operating systems, databases, and applications. The software distinguishes itself through a high-performance architecture that utilizes processor-level vector instructions to perform parallel cryptographic operations. It incorporates a rule-based mutation engine that transforms dictionary words into complex candidates based on
Utilizes processor-level vector instructions to perform multiple cryptographic operations in parallel for significantly increased throughput.
libfacedetection is a C++ face detection library and computer vision tool. It utilizes a neural network face detector to identify human faces in images and return bounding box coordinates. The library is designed for low latency and high throughput processing, enabling real-time face detection in image and video streams. It supports automated image analysis for identifying coordinates of human faces across large batches of photos and high-performance video processing.
Utilizes processor-specific SIMD vector instructions to accelerate neural network mathematical computations.
This project serves as an educational resource for learning and implementing low-level assembly language optimizations. It provides a structured guide for developers to master hardware-specific instructions and manual performance tuning, focusing on the translation of high-level code into efficient machine-level operations for resource-constrained environments. The materials emphasize techniques for maximizing computational throughput in multimedia processing. By covering instruction-level parallelism, register management, and data parallelism, the project enables the development of software
Executes multiple data operations in a single instruction cycle to maximize throughput for high-bandwidth multimedia processing tasks.
TurboVec is a high-performance Rust vector database and quantized search index designed for storing and retrieving high-dimensional embeddings. It functions as a pluggable vector store for large language model orchestration frameworks, providing a memory-efficient alternative to standard in-memory storage. The project distinguishes itself through a high-dimensional vector compressor that utilizes random rotation and data-oblivious scalar quantization to reduce memory footprints. Retrieval is accelerated via SIMD kernels that process distance calculations and search operations for increased th
Accelerates nearest neighbor retrieval using SIMD-accelerated kernels for maximum throughput.
xxHash is a high-performance, non-cryptographic hash library designed for rapid checksum generation and data integrity verification. It functions as an incremental hashing engine, allowing for the processing of large or streaming data inputs by maintaining a persistent internal state across sequential chunks. The library is engineered as a computational framework that maximizes throughput by utilizing wide CPU registers and branchless instruction pipelining. It achieves high-speed performance by aligning data access with CPU cache lines and employing multi-stage mixing functions that ensure c
Processes data in parallel using wide CPU registers to maximize throughput during large memory block hashing operations.
This project is a header-only C++ library designed for graphics mathematics, providing a comprehensive suite of vector, matrix, and quaternion types. It is built using template metaprogramming to generate mathematical primitives at compile time, eliminating the need for precompiled binary libraries and allowing for direct integration into existing build systems. The library is distinguished by its strict adherence to the OpenGL Shading Language specification, ensuring that mathematical results remain consistent across both CPU and GPU code. It provides specialized utilities for managing float
Structures mathematical primitives to align with hardware memory requirements for efficient data access.
This project is an open-source 3D game engine designed for building high-fidelity games, simulations, and cinematic environments. It functions as a robotics simulation platform with native integration for ROS 2 to model robot controllers and sensors. The engine features a multi-threaded Forward+ physically based renderer that supports hardware-accelerated ray tracing and global illumination. The system is built on a modular extension architecture using Gems to add or replace features without modifying core binaries. It includes a native SDK for AWS cloud integration, enabling IAM authenticati
Executes precise mathematical calculations using SIMD-accelerated libraries optimized for x64 and ARM architectures.
JUCE is a comprehensive C++ audio framework and digital signal processing library used to build cross-platform audio applications, audio plug-ins, and high-performance user interfaces. It serves as a development kit for creating audio processors compatible with industry-standard plugin formats for digital audio workstations, as well as a tool for MIDI and Open Sound Control communication between musical hardware and software. The framework is distinguished by its ability to maintain a single codebase for native desktop and mobile applications across multiple operating systems. It provides a f
Employs SIMD vector instructions to perform parallel calculations on audio buffers for higher efficiency.
Thorium is a web browser built from the Chromium project, designed for high performance and expanded compatibility. It utilizes aggressive compiler optimizations and CPU-specific instruction sets, such as AVX2 and SIMD, to increase page rendering and JavaScript execution speeds. The project distinguishes itself by providing custom builds that enable modern web browsing on legacy versions of Windows and Linux. It further diverges from standard browser implementations by integrating Widevine DRM and native support for high-efficiency media formats, including HEVC and JPEG XL. Broad capabilitie
Leverages hardware-level instruction set extensions to accelerate the encryption and decryption of secure web pages.
BLAKE3 是 BLAKE3 加密哈希算法的高性能实现,用于计算安全数据摘要和指纹。它作为一个并行加密哈希工具,将工作负载分布在多个处理器线程上,以快速处理大数据集。 该项目提供用于键控哈希和消息认证码生成的专门工具。它还包括用于加密密钥派生的功能,允许从主密钥和上下文字符串创建唯一的秘密子密钥。 该实现通过并行哈希计算和验证数据流支持数据完整性验证。这些功能作为 Rust 和 C 环境的跨语言库提供,并包含一个用于计算文件或标准输入摘要的命令行界面。
Maximizes CPU throughput by processing multiple data blocks simultaneously using SIMD lanes.
GNU Radio is an open-source software-defined radio framework that provides a digital signal processing toolkit for building wireless communication systems. At its core, it uses a block-based flow graph architecture where pre-built signal processing blocks are connected into directed graphs to define and execute custom radio signal processing pipelines. The system operates as a flow graph signal processor that enables low-latency streaming radio signal processing, supporting both real-time operation and wireless communication simulation entirely in software. The framework distinguishes itself
Uses a vector-optimized library to automatically select CPU-specific SIMD instructions for signal processing.
Gorgonia is a Go library that provides an automatic differentiation engine and a computation graph framework for building and training neural networks. It functions as a CUDA-accelerated tensor library and a SIMD-optimized math library, enabling machine learning workflows entirely within the Go ecosystem. The library distinguishes itself through a dual-backend architecture that dispatches neural network operations to either a GPU or CPU depending on CUDA availability at runtime. It constructs differentiable directed acyclic graphs of tensor operations, supports reverse-mode automatic gradient
Provides SIMD-accelerated float64 vector math as a core performance feature for neural network computations.
Highway 是一个便携式 C++ 库和硬件抽象层,专为编写单指令多数据(SIMD)代码而设计。它提供了一个统一接口,将数据并行逻辑映射到各种 CPU 指令集,从而能够开发出在不同处理器架构上运行的高性能软件,而无需特定于架构的汇编代码。 该项目具有动态指令调度器,可根据检测到的硬件在运行时选择最高效的 CPU 指令集。它还支持静态目标专用化,以及用于添加新硬件目标或自定义 SIMD 操作的可扩展机制。 该库涵盖了广泛的向量操作,包括元素级算术、通道归约、混洗和掩码条件执行。它包括一个向量化数学库、用于对齐分配和掩码加载/存储操作的内存管理器,以及用于硬件加速加密的原语。 提供了用于跨多种处理器架构自动编译和验证硬件加速指令的工具。
Provides a portable interface to write data-parallel code that maps to hardware-accelerated SIMD instructions.
c3c is the compiler for the C3 programming language, transforming source code into executable binaries, static libraries, or dynamic libraries using an LLVM backend. It implements a system based on result-based error handling, scoped memory pooling, and a semantic macro system. The compiler provides first-class support for hardware-backed SIMD vectors that map directly to processor instructions and enables runtime polymorphism through interface-based dynamic dispatch. The project covers a broad set of low-level capabilities, including manual and pooled memory management, inline assembly inte
Executes parallel arithmetic and logical operations on hardware-backed vectors to maximize computational throughput.
ZLinq is a zero-allocation LINQ library and memory-efficient collection toolkit for C#. It provides a high-performance replacement for standard query operations by using value-type enumerators and pooled memory to eliminate heap allocations and reduce garbage collection overhead. The library features a C# source generator that automatically routes standard query method calls to these zero-allocation implementations. It further accelerates data processing through a SIMD accelerated data library, using hardware vectorization for numeric aggregations and bulk operations on primitive arrays and s
Utilizes processor-specific SIMD vector instructions to accelerate numeric aggregations and primitive processing.
Rack 是一个虚拟 Eurorack 模块化合成器模拟器及模块化合成 SDK。它提供了一个数字环境,通过虚拟模块、振荡器和滤波器来创建和路由电子音乐信号,利用基于电压的信号路由模拟模拟硬件的行为。 该系统可作为 MIDI 和 CV 转换器,在软件与外部硬件之间转换信号,并能作为 VST 或行业标准乐器插件在数字音频工作站 (DAW) 中运行。它还充当 VST 插件宿主,嵌入外部虚拟乐器和效果器以扩展声音处理工具。 该平台包含全面的音频处理能力,包括物理建模合成、频谱处理和基于时间的特效。它提供控制电压生成、音符序列化和复音信号处理工具,以及用于构建带有 SVG 驱动界面的自定义音频模块的开发套件。 此外,它还提供命令行界面用于应用启动、项目引导以及从矢量图形自动化生成源文件。
Utilizes SIMD vector instructions to process multiple audio channels in parallel for CPU efficiency.
MiniOB is an open-source educational relational database kernel designed for learning the internals of database systems. It implements a dual-engine storage architecture combining B+ Tree and LSM-Tree, supports SQL parsing and query execution, and provides transactional processing with multi-version concurrency control. The system communicates with clients using the MySQL wire protocol and includes a vector database extension for storing and querying high-dimensional vectors. The project distinguishes itself through its comprehensive coverage of core database concepts in a single, learnable c
Uses single-instruction-multiple-data instructions to speed up arithmetic, aggregation, and hash-table operations on vectorized data chunks.