awesome-repositories.com
Blog
awesome-repositories.com

Descubre los mejores repositorios open-source con nuestra búsqueda potenciada por IA.

ExplorarBúsquedas curadasAlternativas open-sourceSoftware autohospedableBlogMapa del sitio
ProyectoAcerca deCómo clasificamosPrensaServidor MCP
Aviso legalPrivacidadTérminos
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

35 repositorios

Awesome GitHub RepositoriesParallel Task Spawning

Mechanisms for spawning multiple concurrent operations within a shared scope to merge results upon completion.

Distinct from Parallel Task Executors: Distinct from Parallel Task Executors: focuses on scoped parallel spawning rather than dependency-aware build execution.

Explore 35 awesome GitHub repositories matching software engineering & architecture · Parallel Task Spawning. Refine with filters or upvote what's useful.

Awesome Parallel Task Spawning GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • caolan/asyncAvatar de caolan

    caolan/async

    28,150Ver en GitHub↗

    Async is a JavaScript asynchronous flow library designed to manage the execution and coordination of asynchronous tasks in Node.js and the browser. It provides functional utilities to wrap, process, and orchestrate complex asynchronous workflows. The library distinguishes itself through a comprehensive task orchestrator that handles dependency graphs to resolve circular references and manages concurrent task queues. It includes a unification bridge that allows callback-style and promise-based functions to operate within the same execution interface. The project covers several primary capabil

    Spawns multiple concurrent operations within a shared scope and merges all results upon completion.

    JavaScript
    Ver en GitHub↗28,150
  • alibaba/dataxAvatar de alibaba

    alibaba/DataX

    17,241Ver en GitHub↗

    DataX is a distributed data integration framework and plugin-based ETL tool designed for synchronizing large datasets between heterogeneous sources and destinations. It functions as a JDBC data migration engine and offline synchronization tool, enabling the movement of data between relational databases, NoSQL stores, and object storage. The system utilizes a plugin-based connector architecture that decouples reader and writer logic, allowing it to map and transform data types across different storage engines using a standardized internal representation. This design supports heterogeneous data

    Splits large datasets into concurrent tasks based on primary keys to increase synchronization speed.

    Java
    Ver en GitHub↗17,241
  • mxcl/promisekitAvatar de mxcl

    mxcl/PromiseKit

    14,238Ver en GitHub↗

    PromiseKit is a future-based concurrency framework and promise library for Swift and Objective-C. It functions as an asynchronous workflow coordinator, representing the eventual result of an operation to simplify concurrency logic and replace nested callback structures. The framework enables the coordination of both sequential and parallel asynchronous tasks. It provides a structured pipeline for chaining operations, allowing the results of one task to be passed into the next and facilitating the execution of multiple operations simultaneously. The library includes a state-machine based reso

    Spawns multiple concurrent operations within a shared scope and merges their results upon completion.

    Swift
    Ver en GitHub↗14,238
  • rayon-rs/rayonAvatar de rayon-rs

    rayon-rs/rayon

    13,071Ver en GitHub↗

    Rayon is a data parallelism library for Rust that provides a framework for converting sequential computations into parallel operations. It enables the transformation of standard data structures and loops into parallel iterators, allowing workloads to be distributed across multiple processor cores. By utilizing a work-stealing scheduler, the library dynamically balances tasks to maximize throughput and minimize execution time. The library distinguishes itself through its focus on safe, scoped task synchronization, which ensures that all spawned operations complete before a scope exits to preve

    Spawns multiple operations within a shared scope to perform concurrent calculations and merge results.

    Rust
    Ver en GitHub↗13,071
  • morvanzhou/tutorialsAvatar de MorvanZhou

    MorvanZhou/tutorials

    12,952Ver en GitHub↗

    This repository is a comprehensive collection of instructional guides and practical examples for Python development, focusing on machine learning, data science, and web scraping. It provides implementations for neural networks, reinforcement learning algorithms, and deep learning architectures using PyTorch, alongside detailed manuals for scientific computing and data visualization. The project distinguishes itself by offering specialized tutorials on concurrent programming to optimize CPU performance and guides for setting up Linux development environments. It covers the implementation of ad

    Uses process pools to manage collections of worker processes for executing independent functions in parallel.

    Pythonmachine-learningmultiprocessingneural-network
    Ver en GitHub↗12,952
  • coder/coderAvatar de coder

    coder/coder

    12,272Ver en GitHub↗

    Coder is a self-hosted platform for provisioning and managing isolated, containerized development environments. It provides a centralized infrastructure for teams to deploy ephemeral workspaces on private cloud or on-premises hardware, ensuring consistent toolchains and dependencies across distributed development environments. The platform distinguishes itself through its focus on secure, infrastructure-as-code governance and autonomous agent integration. It allows organizations to define reusable, versioned environment templates that integrate with existing identity providers and role-based

    Spawns independent sub-agents to handle concurrent work, maintaining focused context windows and improving performance for complex assignments.

    Goagentsdev-toolsdevelopment-environment
    Ver en GitHub↗12,272
  • cpp-taskflow/cpp-taskflowAvatar de cpp-taskflow

    cpp-taskflow/cpp-taskflow

    12,014Ver en GitHub↗

    Cpp-taskflow is a C++ task-parallelism framework and task graph scheduler designed to manage and execute complex dependency graphs of parallel tasks across CPU and GPU hardware. It provides a parallel algorithm library for high-performance implementations of reductions, sorts, pipelines, and iterations. The framework distinguishes itself through its ability to offload heavy computational workloads from a task graph to graphics processors for acceleration. It also includes a task profiling tool and a performance analysis interface for visualizing task execution flow and dependency structures t

    Supports spawning multiple concurrent operations independently of the main graph to explore runtime parallelism.

    C++
    Ver en GitHub↗12,014
  • tj/coT

    tj/co

    11,856Ver en GitHub↗

    co is a JavaScript generator control flow library and non-blocking workflow engine. It manages asynchronous logic by using generators and promises to simulate a synchronous coding style. The project transforms generator functions into standard functions that return promises, ensuring compatibility with non-generator interfaces. It also functions as a promise-based asynchronous orchestrator that executes multiple operations concurrently through the recursive resolution of nested promise collections. The library provides high-level primitives for asynchronous flow control and non-blocking work

    Resolves nested arrays or objects of promises recursively to ensure complete parallel task execution.

    JavaScript
    Ver en GitHub↗11,856
  • simular-ai/agent-sAvatar de simular-ai

    simular-ai/Agent-S

    11,855Ver en GitHub↗

    Agent-S is a multimodal AI agent and LLM desktop automation framework designed to control operating systems through graphical user interface interactions. It functions as a computer use interface, utilizing vision-language grounding to translate natural language goals into precise screen coordinates and system actions. The project differentiates itself by combining structured accessibility tree inspection with vision-based element localization. It manages cross-application workflows by mapping conceptual descriptions to physical pixels and simulating low-level keyboard and mouse events to mov

    Executes multiple task attempts in parallel to select the most successful outcome.

    Pythonagent-computer-interfaceai-agentscomputer-automation
    Ver en GitHub↗11,855
  • sourcegraph/concAvatar de sourcegraph

    sourcegraph/conc

    10,307Ver en GitHub↗

    conc is a Go concurrency library and structured concurrency framework providing primitives for managing parallel tasks, mapping slices, and collecting results. It implements a system for spawning scoped tasks to ensure all child processes complete before their parent exits. The library includes a goroutine pool manager to limit active concurrent processes and a panic-safe task runner that catches panics in goroutines and propagates stack traces to the parent. It also provides a concurrent map-reduce tool for transforming data slices and processing streams in parallel while maintaining the ori

    Runs a collection of functions concurrently and aggregates results into a single data structure.

    Goconcurrencygogolang
    Ver en GitHub↗10,307
  • microsoft/napajsAvatar de Microsoft

    Microsoft/napajs

    9,180Ver en GitHub↗

    Napajs is an embeddable JavaScript engine and multi-threaded runtime designed to be integrated directly into other software applications as a component. It serves as a parallel computation framework that allows JavaScript code to execute across multiple threads, bypassing the standard single-threaded event loop limitation to handle CPU-intensive tasks. The runtime is distinguished by its ability to load and execute modules from the NPM ecosystem and its pluggable execution environment. This architecture allows for custom implementations of memory allocation, system logging, and performance me

    Distributes recursive operations across multiple threads using promises to prevent deadlocks during sub-task completion.

    C++
    Ver en GitHub↗9,180
  • arkweid/lefthookAvatar de Arkweid

    Arkweid/lefthook

    8,434Ver en GitHub↗

    Lefthook es un gestor de Git hooks y automatizador de flujos de trabajo que utiliza un enfoque basado en configuración para gestionar scripts activados por eventos de control de versiones. Funciona como un ejecutor de tareas en paralelo, ejecutando múltiples scripts simultáneamente para reducir el tiempo requerido para las comprobaciones de pre-commit o pre-push. El proyecto proporciona un ejecutor de hooks contenedorizado para garantizar dependencias y conjuntos de herramientas consistentes en diferentes máquinas de desarrolladores. También admite la orquestación de monorepos ejecutando scripts dentro de subdirectorios específicos y gestionando estructuras de proyectos complejas. El sistema incluye capacidades para el filtrado de archivos basado en patrones para ejecutar tareas de control de calidad solo en activos modificados. Además, admite la ejecución manual de tareas, el etiquetado y agrupación de comandos, y anulaciones de configuración local para ajustes específicos del entorno.

    Executes multiple independent shell commands in parallel to minimize the time spent waiting for hook completion.

    Go
    Ver en GitHub↗8,434
  • crazyguitar/pysheeetAvatar de crazyguitar

    crazyguitar/pysheeet

    8,150Ver en GitHub↗

    pysheeet es una biblioteca de referencia técnica que proporciona una colección curada de fragmentos de código y patrones de implementación para el desarrollo avanzado en Python, integración de sistemas y computación de alto rendimiento. Sirve como una guía completa para implementar programación de red de bajo nivel, extensiones nativas en C y programación asíncrona y concurrente. El proyecto proporciona frameworks especializados para el desarrollo y despliegue de modelos de lenguaje de gran tamaño, incluyendo herramientas para inferencia distribuida en GPU y servicio de alto rendimiento. También incluye patrones detallados para la orquestación de clústeres de computación de alto rendimiento, cubriendo la asignación de recursos de GPU y la gestión de cargas de trabajo en múltiples nodos. La biblioteca cubre una amplia superficie de capacidades, incluyendo comunicación de red segura y criptografía, mapeo objeto-relacional y gestión de bases de datos, y la implementación de estructuras de datos y algoritmos complejos. También proporciona utilidades para la gestión de memoria, interoperabilidad nativa a través de interfaces de funciones externas e integración de sistemas operativos a nivel de sistema.

    Implements patterns for scheduling functions and tracking their status through future-based objects.

    Python
    Ver en GitHub↗8,150
  • rust-lang/rust-by-exampleAvatar de rust-lang

    rust-lang/rust-by-example

    8,026Ver en GitHub↗

    This project is an interactive programming education resource and tutorial designed for learning the Rust programming language and systems programming concepts. It provides a collection of runnable and editable code examples that serve as a practical reference for language syntax and implementation. The resource features an interactive code sandbox that allows users to execute and test code snippets in real time. It emphasizes the verification of technical accuracy by executing embedded code blocks during the build process to ensure all examples remain functional. The content covers a compre

    Teaches how to spawn native operating system threads for parallel task execution.

    Handlebars
    Ver en GitHub↗8,026
  • codebasics/pyAvatar de codebasics

    codebasics/py

    7,262Ver en GitHub↗

    This project is a Python data science curriculum and programming tutorial collection. It provides a structured set of educational notebooks and scripts designed to teach data analysis, machine learning, and deep learning. The repository serves as a learning path for building and tuning predictive models, including regression, decision trees, and neural networks. It includes a data visualization guide for creating financial time-series plots and a multiprocessing reference for implementing parallel task execution and shared memory synchronization. The curriculum covers broader capability area

    Demonstrates how to spawn multiple worker processes to execute functions in parallel and bypass the GIL.

    Jupyter Notebookjupyterjupyter-notebookjupyter-notebooks
    Ver en GitHub↗7,262
  • hyperf/hyperfAvatar de hyperf

    hyperf/hyperf

    6,855Ver en GitHub↗

    Hyperf is a high-performance PHP coroutine framework designed for building microservices and middleware. It utilizes non-blocking coroutines to handle high concurrency and low-latency request processing, providing a foundation for scalable distributed systems. The framework is distinguished by an aspect-oriented programming based dependency injector that enables pluggable components and meta-programming. It includes a coroutine-optimized object-relational mapper with integrated model caching and an orchestration toolkit for microservice governance, featuring service discovery, circuit breaker

    Enables running multiple callbacks concurrently to execute independent operations in parallel and merge their results.

    PHP
    Ver en GitHub↗6,855
  • uxlfoundation/onetbbAvatar de uxlfoundation

    uxlfoundation/oneTBB

    6,678Ver en GitHub↗

    oneAPI Threading Building Blocks (oneTBB)

    Documents migration paths from low-level task APIs to higher-level constructs like task groups and parallel invocations.

    C++composabilityflowgraphheterogeneousprogramming
    Ver en GitHub↗6,678
  • gevent/geventAvatar de gevent

    gevent/gevent

    6,440Ver en GitHub↗

    Gevent is a Python coroutine concurrency library and asynchronous task manager designed for high-concurrency I/O tasks. It provides a cooperative networking framework for building asynchronous TCP, UDP, and HTTP servers, as well as a WSGI web server implementation for hosting web applications. The project is distinguished by its standard library monkey-patching tool, which replaces blocking synchronous functions with cooperative versions to enable asynchronous behavior in third-party code. This allows for a cooperative multitasking workflow where the system yields execution during I/O waits t

    Distributes work across thread pools using mapping methods that support recursive calls and exception propagation.

    Pythonasynciocoroutinesgreenlet
    Ver en GitHub↗6,440
  • dimitri/pgloaderAvatar de dimitri

    dimitri/pgloader

    6,295Ver en GitHub↗

    pgloader is a command-line tool that automates the migration of data and schema from various source databases and file formats into PostgreSQL. It combines schema discovery, parallel data pipelines, and type casting into a single, declarative workflow, using PostgreSQL's COPY protocol for high-throughput bulk loading. The tool distinguishes itself by compiling a dedicated command language into concurrent reader-writer pipelines that handle schema introspection, data transformation, and error-resilient batch processing. It supports migrating entire databases from MySQL, MS SQL, SQLite, and Pos

    Spawns multiple concurrent threads that each read a disjoint range of source data, transform it, and feed it into a dedicated COPY stream.

    Common Lispclozure-clcommon-lispcsv
    Ver en GitHub↗6,295
  • balloonwj/cppguideAvatar de balloonwj

    balloonwj/CppGuide

    6,030Ver en GitHub↗

    CppGuide is a curated collection of educational resources and practical guides focused on C++ server development, Linux kernel internals, concurrent programming, network protocols, and security exploitation. It provides structured learning paths for backend developers, covering everything from interview preparation to building high-performance network servers and understanding operating system fundamentals. The guide distinguishes itself by offering in-depth, hands-on tutorials that walk through real-world implementations, including building a Redis-like server from scratch, designing custom

    Describes how the kernel creates its first thread and initial user-space process during boot.

    Ver en GitHub↗6,030
Ant.12Siguiente
  1. Home
  2. Software Engineering & Architecture
  3. Task Scheduling
  4. Parallel Task Executors
  5. Parallel Task Spawning

Explorar subetiquetas

  • Async Context SpawningSpawns a future to completion from inside async functions, closures, or blocks using a macro. **Distinct from Parallel Task Spawning:** Distinct from Parallel Task Spawning: focuses on spawning futures from within async contexts, not scoped parallel execution.
  • Async Task Spawning2 sub-etiquetasTraits and macros for spawning and driving asynchronous futures to completion on executors. **Distinct from Parallel Task Spawning:** Distinct from Parallel Task Spawning: focuses on async future spawning with executor traits, not general parallel operation spawning.
  • Event Loop SchedulersSchedules multiple I/O operations on an event loop that resumes each task upon completion. **Distinct from Parallel Task Spawning:** Distinct from Parallel Task Spawning: focuses on event-loop-based resumption rather than scoped parallel spawning.
  • Higher-Level Task API MigrationsReplace direct task spawning and scheduling with higher-level constructs like task groups and parallel invocations. **Distinct from Parallel Task Spawning:** Distinct from Parallel Task Spawning: focuses on migrating from low-level APIs to higher-level constructs, not the spawning mechanism itself.
  • Model Grid SpawningConcurrent spawning of multiple model instances into a grid-based visual layout. **Distinct from Parallel Task Spawning:** Focuses on the visual grid arrangement of spawned models rather than generic concurrent operation spawning.
  • OS Thread Spawning2 sub-etiquetasCreating execution units directly managed by the operating system scheduler. **Distinct from Parallel Task Spawning:** Focuses on native OS threads specifically, whereas Parallel Task Spawning is more general about concurrent operations.
  • Parallel Data PipelinesSpawns multiple concurrent threads that each read a disjoint range of source data, transform it, and feed it into a dedicated COPY stream. **Distinct from Parallel Task Spawning:** Distinct from Parallel Task Spawning: focuses on data pipeline parallelism with disjoint ranges and COPY streams, not general task spawning.
  • Parallel Task SynchronizationCoordinating the completion of multiple parallel tasks using counters or timeout mechanisms. **Distinct from Parallel Task Spawning:** Focuses on the synchronization/joining phase of parallel tasks rather than the spawning process.
  • Process PoolsManagement of a fixed set of worker processes to execute independent functions in parallel. **Distinct from Parallel Task Spawning:** Specifically concerns the use of process pools for parallel function execution rather than general scoped spawning
  • Recursive Parallel Distribution1 sub-etiquetaDistributing recursive operations across multiple threads to avoid deadlocks during sub-task completion. **Distinct from Parallel Task Spawning:** Focuses specifically on recursive workload distribution via promises, whereas the candidate is generic scoped spawning.
  • Success-Based Parallel SamplingMechanisms for spawning concurrent task attempts to merge and select the most successful outcome. **Distinct from Parallel Task Spawning:** Distinct from general spawning by its focus on outcome selection for optimization.