1291 projects for "computing" with 1 filter applied:

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  • 1
    Papers We Love

    Papers We Love

    Papers from the computer science community to read and discuss

    Papers We Love (PWL) is a global open source community dedicated to reading, discussing, and sharing influential computer science research papers. The repository serves as a curated directory of academic papers that have shaped the field of computing, providing a centralized location for documents that were previously scattered across various online sources. While licensing restrictions prevent hosting all papers directly, PWL offers links to their original sources and clearly marks hosted copies with an emoji. The community encourages participation through local meetups, where members gather to discuss and analyze key works spanning topics such as programming languages, distributed systems, and software engineering. ...
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  • 2
    Matcha-TTS

    Matcha-TTS

    A fast TTS architecture with conditional flow matching

    ...The repository provides an end-to-end TTS pipeline: a PyTorch/Lightning training stack, configuration files, pre-trained checkpoints, a command-line interface, and a Gradio app for interactive testing. Users can train on standard datasets like LJSpeech or plug in their own corpora, with helper tools for computing dataset statistics, extracting phoneme durations, and running multi-GPU training.
    Downloads: 1 This Week
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  • 3
    Retro UI

    Retro UI

    A NeoBrutalism styled React + TailwindCSS UI library

    Retro UI is a design-focused UI library that recreates classic retro computing aesthetics within modern web interfaces, offering developers a way to build nostalgic, vintage-style applications. It provides components styled to resemble old operating systems and early graphical user interfaces, including elements like pixelated buttons, window frames, and low-resolution typography. The project is aimed at developers and designers who want to create unique user experiences that stand out from contemporary flat or minimal design trends. ...
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  • 4
    TensorFlow Quantum

    TensorFlow Quantum

    Open-source Python framework for hybrid quantum-classical ml learning

    ...By combining classical deep learning techniques with quantum algorithms, the platform allows experimentation with quantum machine learning methods that may offer advantages for certain computational tasks. TensorFlow Quantum integrates with the Cirq quantum computing framework to define and manipulate quantum circuits, while leveraging TensorFlow’s infrastructure for optimization, automatic differentiation, and large-scale computation. The library also supports high-performance simulation of quantum circuits, enabling researchers to test and evaluate quantum models even without direct access to quantum hardware.
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  • 5
    TAME LLM

    TAME LLM

    Traditional Mandarin LLMs for Taiwan

    ...These models are designed to support applications such as conversational AI, knowledge retrieval, and domain-specific reasoning in fields like manufacturing, law, healthcare, and electronics. The training pipeline leverages high-performance computing infrastructure and frameworks such as NVIDIA NeMo and Megatron to enable large-scale model training. Taiwan-LLM aims to improve language understanding and generation for Traditional Mandarin users by incorporating region-specific datasets and evaluation benchmarks.
    Downloads: 0 This Week
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  • 6
    Chitu

    Chitu

    High-performance inference framework for large language models

    ...The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations. Chitu is designed to scale from small single-machine deployments to large distributed clusters that handle high volumes of concurrent inference requests. The system also includes performance optimizations for large models, including support for quantized formats and efficient computation operators that reduce memory usage and latency. ...
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  • 7
    Chat with LLMs Everywhere

    Chat with LLMs Everywhere

    Run PyTorch LLMs locally on servers, desktop and mobile

    TorchChat is an open-source project from the PyTorch ecosystem designed to demonstrate how large language models can be executed efficiently across different computing environments. The project provides a compact codebase that illustrates how to run conversational AI systems using PyTorch models on laptops, servers, and mobile devices. It is intended primarily as a reference implementation that shows developers how to integrate large language models into applications without requiring a large or complex infrastructure stack. ...
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  • 8
    Xtuner

    Xtuner

    A Next-Generation Training Engine Built for Ultra-Large MoE Models

    Xtuner is a large-scale training engine designed for efficient training and fine-tuning of modern large language models, particularly mixture-of-experts architectures. The framework focuses on enabling scalable training for extremely large models while maintaining efficiency across distributed computing environments. Unlike traditional 3D parallel training strategies, XTuner introduces optimized parallelism techniques that simplify scaling and reduce system complexity when training massive models. The engine supports training models with hundreds of billions of parameters and enables long-context training with sequence lengths reaching tens of thousands of tokens. ...
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  • 9
    KubeEdge

    KubeEdge

    Kubernetes Native Edge Computing Framework (project under CNCF)

    KubeEdge is built upon Kubernetes and extends native containerized application orchestration and device management to hosts at the Edge. It consists of a cloud part and an edge part, and provides core infrastructure support for networking, application deployment, and metadata synchronization between the cloud and edge. It also supports MQTT which enables edge devices to access through edge nodes. With KubeEdge it is easy to get and deploy existing complicated machine learning, image...
    Downloads: 0 This Week
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  • 10
    Measurements.jl

    Measurements.jl

    Error propagation calculator and library for physical measurements

    Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration. Physical measures are typically reported with an error, a quantification of the uncertainty of the accuracy of the measurement. Whenever you perform mathematical operations involving these quantities you have also to propagate the uncertainty, so that the resulting number will also have...
    Downloads: 0 This Week
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  • 11
    E2B Cookbook

    E2B Cookbook

    Examples of using E2B

    ...The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code execution, and application generation inside isolated sandbox environments. E2B itself provides secure Linux-based sandboxes that enable AI systems to safely run generated code and interact with real computing resources without compromising the host environment. The cookbook organizes examples across multiple frameworks and model providers, allowing developers to experiment with integrations involving models from OpenAI, Anthropic, and other ecosystems.
    Downloads: 0 This Week
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  • 12
    Apache Seata

    Apache Seata

    High-performance, open source distributed transaction solution

    Seata is a distributed transaction solution for microservices that provides consistent, cross-service commits without forcing every team to adopt the same persistence model. Its architecture separates responsibilities into a global coordinator and per-service participants, so business services remain decoupled while transactions are orchestrated centrally. Multiple modes are supported—AT (automatic, SQL-based with undo logs), TCC (try-confirm-cancel), Saga (long-running compensation), and...
    Downloads: 0 This Week
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  • 13
    Matrix

    Matrix

    Multi-Agent daTa geneRation Infra and eXperimentation framework

    Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous, peer-to-peer agent workflows, avoiding global synchronization bottlenecks. That design makes Matrix particularly well-suited for large-batch inference, model benchmarking, data curation, augmentation, or generation — whether for language, code, dialogue, or multimodal tasks. ...
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  • 14
    Project MINI RACK

    Project MINI RACK

    Miniature rack builds, for portable or compact Homelabs

    Project MINI RACK is a project dedicated to designing, documenting, and showcasing compact, portable rack-mount or small-form factor “mini” labs, suitable for home labs, edge deployments, or mobile network stacks. The repository contains build guides, hardware lists, layout ideas (10” wide racks, 1U/2U modules, custom shelves), 3D printable components, and real-world examples of mini homelab rigs. Its goal is to help hobbyists, devops engineers, or tinkerers understand how to build...
    Downloads: 0 This Week
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  • 15
    openQRM - Cloud Computing Platform

    openQRM - Cloud Computing Platform

    Get latest Edition here: http://www.openqrm-enterprise.com.

    openQRM is a web-based open source datacenter management and hybrid cloud computing platform that integrates flexibly with existing components in enterprise data centers. Releases available at https://github.com/openQRM/openqrm-community. Please visit http://www.openqrm-enterprise.com for latest 5.3 free Community Release. Includes important security updates, bugfixes and enhancements especially for KVM and Cloud plugin.
    Downloads: 0 This Week
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  • 16
    mlforecast

    mlforecast

    Scalable machine learning for time series forecasting

    ...It supports multi-series forecasting, meaning you can train one model that forecasts many time series at once (common in retail, demand forecasting, etc.), rather than one model per series. The library is built to scale: behind the scenes, it can leverage distributed computing frameworks (Spark, Dask, Ray) when datasets or the number of series grow large.
    Downloads: 0 This Week
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  • 17
    ProbabilisticCircuits.jl

    ProbabilisticCircuits.jl

    Probabilistic Circuits from the Juice library

    ...PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units). Given certain structural properties, PCs enable different range of tractable exact probabilistic queries such as computing marginals, conditionals, maximum a posteriori (MAP), and more advanced probabilistic queries.
    Downloads: 0 This Week
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  • 18
    UNICORE

    UNICORE

    UNiform Interface to COmputing and data REsources

    UNICORE is a software suite for building federated systems, providing secure and seamless access to heterogeneous resource such as compute clusters and file systems. UNICORE deals with authentication, user mapping and authorization, and provides a comprehensive set of RESTful APIs for HPC access and workflows. Contributors: visit https://github.com/UNICORE-EU
    Downloads: 30 This Week
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  • 19
    DelphiWebStart
    DelphiWebStart (DWS) is an Application Loader with TCP Sockets based on a ThinClient first spread over the Web, VPN or Intranet. So a user can download data (exes, maps, files) from a list and start it. DWS supports OpenSSL including a PKI HTTPS-Server.
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    Downloads: 59 This Week
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  • 20
    OpenFOAM

    OpenFOAM

    The Open Source CFD Toolbox

    OpenFOAM - The Open Source CFD Toolbox. OpenFOAM is a generic, programmable software tool for Computational Fluid Dynamics (CFD). For more information, see: - Main Website: https://openfoam.org - C++ Source Documentation: https://cpp.openfoam.org - Issue (Bug) Tracking: https://bugs.openfoam.org - User Guide: https://cfd.direct/openfoam/user-guide
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    Downloads: 3,592 This Week
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  • 21
    Armadillo

    Armadillo

    fast C++ library for linear algebra & scientific computing

    * Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc
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    Downloads: 2,747 This Week
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  • 22
    RHash
    RHash (Recursive Hasher) is a console utility for computing and verifying hash sums of files. It supports CRC32, CRC32C, MD4, MD5, SHA1, SHA256, SHA512, SHA3, AICH, ED2K, DC++ TTH, BTIH, Tiger, GOST R 34.11-2012, RIPEMD-160, HAS-160, EDON-R, and Whirlpool.
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    Downloads: 921 This Week
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  • 23

    bootf2BCA

    computing f2 bootstrap CI BCA

    Computing similarity factor (f2) bootstrap bias corrected and accelerated confidence interval
    Downloads: 16 This Week
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  • 24
    Quantum Information Toolkit is a comprehensive, easy-to-use interactive numerical toolkit for quantum information and computing, available for both MATLAB and Python.
    Downloads: 0 This Week
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  • 25
    migrid

    migrid

    A grid middleware with minimal user and resource requirements

    [This project moved to Github and is no longer maintained here] Minimum intrusion Grid (MiG) is an attempt to design a new platform for Grid computing which is driven by a stand-alone approach to Grid, rather than integration with existing systems. The goal of the MiG project is to provide Grid infrastructure where the requirements on users and resources alike is as small as possible (minimum intrusion). MiG strives for minimum intrusion but will seek to provide a feature rich and dependable Grid solution. ...
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