Search Results for "high" - Page 30
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Showing 5833 open source projects for "high"
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clip-retrieval
Easily compute clip embeddings and build a clip retrieval system
clip-retrieval is an open-source toolkit designed to build large-scale semantic search systems for images and text by leveraging CLIP embeddings to enable multimodal retrieval. It allows developers to compute embeddings for both images and text efficiently and then index them for fast similarity search across massive datasets. The system is optimized for performance and scalability, capable of processing tens or even hundreds of millions of embeddings using GPU acceleration. It includes... -
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ZML
Any model. Any hardware. Zero compromise
ZML is a high-performance machine learning inference stack designed to run AI models efficiently across heterogeneous hardware environments using a modern systems programming approach. Built with technologies such as Zig, MLIR, and Bazel, it focuses on production-grade deployment where performance, portability, and scalability are critical. The system allows models to be compiled and executed across multiple types of accelerators, including GPUs and TPUs, even when distributed across different machines or locations. ... -
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CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory layouts, parallelism, and execution patterns while still maintaining a developer-friendly syntax. ... -
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LitServe
Minimal Python framework for scalable AI inference servers fast
...LitServe is built on top of FastAPI and extends it with AI-specific optimizations such as efficient multi-worker execution, which can significantly improve throughput. It includes built-in capabilities for batching, streaming responses, and automatic scaling across CPUs and GPUs, enabling high-performance deployments. -
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Browserless
The headless Chrome/Chromium driver on top of Puppeteer
Browserless is an open-source headless browser automation library and service built on top of Puppeteer that simplifies the process of running and scaling Chromium-based browser tasks in production environments. It provides a high-level API for interacting with headless Chrome, allowing developers to perform operations such as generating PDFs, capturing screenshots, extracting text or HTML, and automating web navigation. The project is designed to act as a production-ready abstraction layer over Puppeteer, offering improved reliability, error handling, and scalability for real-world applications. ... -
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Situation Monitor
Real-time dashboard for monitoring global news and markets
Situation Monitor is an open-source real-time dashboard designed to aggregate and visualize global information streams related to news, financial markets, technology, and geopolitical developments. The project aims to provide a centralized situational awareness interface where users can observe multiple sources of high-signal information without constantly switching between separate applications or websites. Instead of functioning as a traditional news reader, the platform is designed more like an intelligence monitoring system that highlights important signals from diverse data feeds. The dashboard aggregates real-time updates about economic indicators, corporate developments, geopolitical events, and other macro-level signals that may influence markets or public discourse. ... -
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OpenFang
Open-source Agent Operating System
OpenFang is an open-source agent operating system designed to orchestrate autonomous AI agents and workflows in a structured, production-oriented environment. Written primarily in Rust, the project focuses on building a high-performance runtime where multiple specialized agents can collaborate to complete complex computational or development tasks. It aims to move beyond simple chat-based agents by providing infrastructure for persistent agent memory, task coordination, and scalable execution. The system is positioned as a foundation for building advanced AI tooling, particularly in environments that require tight integration with GPU workflows and modern AI pipelines. ... -
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MemOS
AI memory OS for LLM and Agent systems
...By abandoning some of the historical assumptions of Unix-style operating systems, MemOS attempts to unlock new performance and scalability tradeoffs for applications that need high throughput and low latency on memory-intensive workloads. -
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TONL
TONL (Token-Optimized Notation Language)
...The platform comes with a complete command-line interface that supports interactive dashboards and cross-platform usage in browsers and server environments, and its high test coverage gives developers confidence in stability. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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GoDoxy
High-performance reverse proxy and container orchestrator
GoDoxy is a high-performance reverse proxy and container orchestrator tailored for self-hosting environments, blending automated routing with a user-friendly web interface and advanced traffic control. Written in Go, it automatically discovers services (like Docker containers) and generates routes based on configuration or container labels, letting you expose and secure apps with minimal manual routing. -
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LiveAvatar
Streaming Real-time Audio-Driven Avatar Generation
...The project co-designs algorithms and system optimizations, such as block-wise autoregressive processing and fast sampling strategies, to deliver real-time frame rates (e.g., ~45 FPS on appropriate GPU clusters) while handling non-stop generation without quality degradation. LiveAvatar focuses on delivering not just high-quality visuals but also the responsiveness necessary for immersive conversational experiences, making it suitable for advanced AI agents, virtual assistants, and interactive streaming contexts. -
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MongoDB PHP Library
The Official MongoDB PHP library
The MongoDB PHP Library is the official high-level library that lets PHP applications interact with MongoDB using a modern, expressive API. It provides object-oriented classes for databases, collections, queries, and operations, so PHP developers can compose CRUD and aggregation pipelines without writing low-level protocol code. Built on top of the underlying MongoDB PHP extension, the library handles serialization, connection pooling, and error handling in a way that feels natural in idiomatic PHP. ... -
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Motor
The async Python driver for MongoDB and Tornado or asyncio
Motor is an asynchronous Python driver for MongoDB that enables developers to work with MongoDB using non-blocking I/O patterns, making it ideal for high-performance and scalable applications. Built on top of Python’s Tornado and asyncio frameworks, Motor lets you issue database operations without blocking the event loop, enabling concurrency in web servers, real-time systems, and microservices. It provides a familiar API surface similar to the official synchronous PyMongo driver, so you can migrate or write MongoDB code in Python without having to learn a completely new interface. ... -
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Minigrid
Simple and easily configurable grid world environments
...While it is not a full 3D simulation environment, its strength lies in enabling many environment resets and steps cheaply, which is valuable for algorithmic RL research rather than high-fidelity rendering. -
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Solon
Java enterprise application development framework
Solon is a full-scenario Java enterprise application framework that positions itself as a lean, high-performance alternative to heavy stacks. It advertises large concurrency gains, lower memory use, much faster startup, and dramatically smaller packages while remaining compatible from Java 8 through Java 24. The framework focuses on restrained APIs and an open ecosystem, with modules that cover web, data, cloud, and microservice patterns. -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. -
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webgl-plot
A high-Performance real-time 2D plotting library based on native WebGL
webgl-plot is a high-performance plotting library for real-time data visualization in the browser using WebGL. Unlike traditional canvas or SVG-based charting libraries, webgl-plot is optimized for streaming and dynamic updates, making it ideal for oscilloscope-style data, biomedical signals, or any application where data updates hundreds of times per second. -
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OGRE-Next 3D
aka ogre v2 - scene-oriented, flexible 3D C++ engine
OGRE-Next is the next-generation iteration of the OGRE (Object-Oriented Graphics Rendering Engine), a powerful open-source 3D rendering engine designed for real-time applications, games, simulations, and visualizations. It focuses on high-performance rendering pipelines, especially Vulkan and modern OpenGL, offering tools for photorealistic and stylized rendering. OGRE-Next is modular and flexible, providing a developer-friendly environment with scene management, lighting, shadowing, and post-processing features. With improved performance and a focus on modern graphics APIs, it's ideal for developers building next-gen 3D engines or simulations. -
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Corosync Cluster Engine
The Corosync Cluster Engine
...A quorum system that notifies applications when a quorum is achieved or lost. Our project is used as a high-availability framework by projects such as Pacemaker and Asterisk. We are always looking for developers or users interested in clustering or participating in our project. -
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OpenMLDB
OpenMLDB is an open-source machine learning database
...However, a feature engineering script developed by data scientists (Python scripts in most cases) cannot be directly deployed into production for online inference because it usually cannot meet the engineering requirements, such as low latency, high throughput and high availability. -
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UMAP
Uniform Manifold Approximation and Projection
...The embedding is found by searching for a low-dimensional projection of the data that has the closest possible equivalent fuzzy topological structure. First of all UMAP is fast. It can handle large datasets and high dimensional data without too much difficulty, scaling beyond what most t-SNE packages can manage. This includes very high dimensional sparse datasets. UMAP has successfully been used directly on data with over a million dimensions. Second, UMAP scales well in the embedding dimension—it isn't just for visualization. You can use UMAP as a general-purpose dimension reduction technique as a preliminary step to other machine learning tasks. -
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Operator SDK
SDK for building Kubernetes applications. Provides high level APIs
The Operator SDK makes it easier to build Kubernetes native applications, a process that can require deep, application-specific operational knowledge. The Operator SDK provides the tools to build, test, and package Operators. Initially, the SDK facilitates the marriage of an application’s business logic (for example, how to scale, upgrade, or backup) with the Kubernetes API to execute those operations. Over time, the SDK can allow engineers to make applications smarter and have the user... -
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LinearSolve.jl
High-Performance Unified Interface for Linear Solvers in Julia
...It interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. Performance is key: the current methods are made to be highly performant on scalar and statically sized small problems, with options for large-scale systems. If you run into any performance issues, please file an issue. -
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OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE)
...The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research that routinely outperform the “standard” C/Fortran methods, and include algorithms optimized for high-precision and HPC applications. At the same time, it wraps the classic C/Fortran methods, making it easy to switch over to them whenever necessary. Solving differential equations with different methods from different languages and packages can be done by changing one line of code, allowing for easy benchmarking to ensure you are using the fastest method possible. -
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Makie
Interactive data visualizations and plotting in Julia
...The backend packages GLMakie, WGLMakie, CairoMakie and RPRMakie add different functionalities: You can use Makie to interactively explore your data and create simple GUIs in native Windows or web browsers, export high-quality vector graphics or even raytrace with physically accurate lighting. Choose one or more backend packages: GLMakie (interactive OpenGL in native OS windows), WGLMakie (interactive WebGL in browsers, IDEs, notebooks), CairoMakie (static 2D vector graphics and images), and RPRMakie (raytracing). Each backend re-exports all of Makie.jl so you don't have to install or load it explicitly.
