Search Results for "vector linux"
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Showing 230 open source projects for "vector linux"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Vector Element
A glossy Matrix collaboration client for the web
Protect the most sensitive parts of your organization; from senior executive discussion to intellectual property and cybersecurity. An entire communications platform under your control, with end-to-end encrypted voice, video, messaging and collaboration. Easily scales to serve the largest of organizations, supply chains and entire ecosystems. Support thousands of users in a single end-to-end encrypted chat room. Connect millions in real time across multiple organizations. Decentralization... -
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React Native Vector Icons
Customizable Icons for React Native with full styling
Perfect for buttons, logos and nav/tab bars. Easy to extend, style and integrate into your project. If you want to use any of the bundled icons, you need to add the icon fonts to your Xcode project. For each platform (iOS/Android/Windows) you plan to use, follow one of the options for the corresponding platform. Upgrading this package often requires the font files linked to your projects to be updated as well. If the automatic linking works for you, running this again should update the... -
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RuVector
Self-Learning, Vector Graph Neural Network, and Database built in Rust
RuVector is part of the broader rUv ecosystem of AI engineering tools and focuses on enabling advanced vector-based processing and intelligent system development within agentic and AI-driven pipelines. The project fits into a larger vision of modular, composable AI infrastructure designed to support autonomous agents, data retrieval, and intelligent automation workflows. It emphasizes extensibility and interoperability with modern AI stacks, allowing developers to integrate vector operations... -
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glMatrix
Javascript Matrix and Vector library for High Performance WebGL apps
Javascript has evolved into a language capable of handling realtime 3D graphics, via WebGL, and computationally intensive tasks such as physics simulations. These types of applications demand high performance vector and matrix math, which is something that Javascript doesn't provide by default. glMatrix to the rescue! glMatrix is designed to perform vector and matrix operations stupidly fast! By hand-tuning each function for maximum performance and encouraging efficient usage patterns... -
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Vespa
The open big data serving engine
Make AI-driven decisions using your data, in real-time. At any scale, with unbeatable performance. Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do.... -
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OpenBLAS
Optimized BLAS library based on GotoBLAS2 1.13 BSD version
OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. The Level 1 BLAS performs scalar, vector and vector-vector operations, the Level 2 BLAS performs matrix-vector operations, and the Level 3 BLAS performs matrix-matrix operations. Because the BLAS are efficient, portable, and widely available, they are commonly used in the... -
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DeepMatch
A deep matching model library for recommendations & advertising
DeepMatch is an open-source deep matching library built for recommendation and advertising systems. It helps developers train models that learn vector representations for users and items. These representations can be exported and used in approximate nearest neighbor search for large-scale retrieval. The library supports familiar Keras workflows through model.fit() and model.predict(). Its model collection includes FM, DSSM, YouTubeDNN, NCF, SDM, MIND, and ComiRec. It is designed to make... -
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Google Highway
Performance-portable, length-agnostic SIMD with runtime dispatch
Google Highway is a high-performance C++ library designed to provide portable SIMD (Single Instruction, Multiple Data) vectorization across multiple CPU architectures while maintaining predictable and efficient behavior. It abstracts low-level vector intrinsics into a consistent API that maps closely to hardware instructions, allowing developers to write high-performance code without relying heavily on compiler auto-vectorization. Highway enables the same source code to run across different... -
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Font Awesome
Get vector icons and social logos for your website or blog
Font Awesome was created in a successful Kickstarter and is an easy way for web developers to add icons and logos to their website. There is both a free version and a pro version for extra features and icons. You can support the developers by buying a custom FontAwesome T-Shirt! https://fontawesome.com/shirts -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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HLSL++
Math library using HLSL syntax with multiplatform SIMD support
HLSL++ is a header-only C++ math library designed to replicate the syntax and functionality of the HLSL shading language, making it easier for developers to write CPU-side code that mirrors GPU shader logic. It provides vector, matrix, and math operations with a syntax identical or very similar to HLSL, allowing seamless transition between shader code and application code. The library is optimized for performance and supports SIMD instructions across multiple architectures, including SSE,... -
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ispc
Intel SPMD Program Compiler
ispc is a compiler for a variant of the C programming language, with extensions for single programs, and multiple data programming. Under the SPMD model, the programmer writes a program that generally appears to be a regular serial program, though the execution model is actually that a number of program instances execute in parallel on the hardware. ispc compiles a C-based SPMD programming language to run on the SIMD units of CPUs and GPUs; it frequently provides a 3x or more speedup on... -
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PageIndex
Document Index for Vectorless, Reasoning-based RAG
PageIndex is an innovative open-source framework that reimagines retrieval-augmented generation (RAG) by eliminating conventional vector similarity search and instead building hierarchical semantic indexes that mirror a document’s natural structure. Rather than chunking text and embedding it into a vector database, PageIndex constructs a tree-structured index — similar to a detailed, AI-enhanced table of contents — that a large language model can traverse to locate the most relevant sections... -
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Raglite
RAGLite is a Python toolkit for Retrieval-Augmented Generation
Raglite is a lightweight framework for building Retrieval-Augmented Generation (RAG) pipelines with minimal configuration. It connects large language models to vector databases for context-aware responses, enabling developers to prototype and deploy RAG systems quickly. Raglite focuses on simplicity and modularity for fast experimentation. -
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GraphEmbedding
Implementation and experiments of graph embedding algorithms
GraphEmbedding is an open-source Python project for implementing and experimenting with graph embedding algorithms. It follows a simple “graph in, embedding out” design. The library uses NetworkX graphs as input and produces vector representations for graph nodes. It includes implementations of DeepWalk, LINE, Node2Vec, SDNE, and Struc2Vec. Users can configure walks, embedding dimensions, training windows, epochs, and other model-specific parameters. Example scripts demonstrate how to train... -
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JOML
A Java math library for OpenGL rendering calculations
JOML is a high-performance, lightweight math library designed for 3D graphics applications in Java, particularly those using OpenGL, Vulkan, or LWJGL. It provides a complete suite of vector, matrix, quaternion, and geometry operations essential for real-time graphics and game development. Unlike other math libraries, JOML avoids object allocation during calculations, making it highly optimized for garbage-free performance. With precise control over mathematical operations and compatibility... -
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LLPhant
A comprehensive PHP Generative AI Framework
LLPhant is a PHP-based generative AI framework designed to bring large language model capabilities into modern PHP applications with a structure inspired by frameworks like LangChain. It provides developers with a set of abstractions for building AI-powered features such as chat systems, retrieval pipelines, and automated workflows while remaining simple enough to integrate into existing Symfony or Laravel projects. The framework focuses on usability by offering straightforward APIs for... -
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LangChainGo
LangChain for Go, the easiest way to write LLM-based programs in Go
LangChainGo is a Go-based implementation of the LangChain framework, designed to help developers build applications powered by large language models using the Go programming language. It provides a modular architecture that allows developers to combine components such as language models, chains, agents, memory systems, and vector stores into flexible workflows. The framework emphasizes composability, making it easy to create complex pipelines that integrate LLMs with external data sources,... -
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typst.ts
Run Typst in JavaScriptWorld
typst.ts is a project that brings the Typst typesetting system into the JavaScript ecosystem, enabling document compilation and rendering directly in browser and Node.js environments. It provides an implementation of Typst’s execution environment along with tools for compiling documents into various output formats, including vector graphics and web-friendly representations. The system is designed to support both client-side and server-side rendering workflows, allowing flexible deployment... -
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txtai
Build AI-powered semantic search applications
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid... -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
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Faiss
Library for efficient similarity search and clustering dense vectors
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It... -
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Vector Pascal is a language targeted at SIMD multi-core instruction-sets such as the AVX and SSE2 or x86-64-v3. It has a SIMD compiler which supports parallel vector operations, loop unrolling, common sub expression removal etc. It is implemented in Java.
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XiangShan
Open-source high-performance RISC-V processor
XiangShan is an open-source, high-performance RISC-V processor project that implements out-of-order superscalar cores using Chisel for hardware construction. The design targets modern performance goals—deep pipelines, speculative execution, multi-issue decode/execute, and sophisticated branch prediction—while remaining synthesizable for ASIC flows and portable to FPGAs for research. A modular microarchitecture separates frontend, backend, and memory subsystems with coherent caches and... -
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LangChain.dart
Build LLM-powered Dart/Flutter applications
LangChain.dart is a Dart and Flutter implementation of the LangChain framework, designed to enable developers to build LLM-powered applications for mobile, web, and cross-platform environments. It provides a structured way to integrate language models into applications by offering abstractions for chains, agents, embeddings, and vector stores. The framework supports multiple providers and includes packages for integrating with services such as OpenAI, Google AI, and Firebase, allowing... -
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Earth Engine API
Python and JavaScript bindings for calling the Earth Engine API
The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. Developers authenticate once, work interactively in...
