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34 Repos

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

Awesome Parallel Task Spawning GitHub Repositories

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  • caolan/asyncAvatar von caolan

    caolan/async

    28,150Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗28,150
  • alibaba/dataxAvatar von alibaba

    alibaba/DataX

    17,241Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗17,241
  • mxcl/promisekitAvatar von mxcl

    mxcl/PromiseKit

    14,238Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗14,238
  • rayon-rs/rayonAvatar von rayon-rs

    rayon-rs/rayon

    13,071Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗13,071
  • morvanzhou/tutorialsAvatar von MorvanZhou

    MorvanZhou/tutorials

    12,952Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗12,952
  • coder/coderAvatar von coder

    coder/coder

    12,272Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗12,272
  • cpp-taskflow/cpp-taskflowAvatar von cpp-taskflow

    cpp-taskflow/cpp-taskflow

    12,014Auf GitHub ansehen↗

    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++
    Auf GitHub ansehen↗12,014
  • tj/coT

    tj/co

    11,856Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗11,856
  • simular-ai/agent-sAvatar von simular-ai

    simular-ai/Agent-S

    11,855Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗11,855
  • sourcegraph/concAvatar von sourcegraph

    sourcegraph/conc

    10,307Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗10,307
  • microsoft/napajsAvatar von Microsoft

    Microsoft/napajs

    9,180Auf GitHub ansehen↗

    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++
    Auf GitHub ansehen↗9,180
  • arkweid/lefthookAvatar von Arkweid

    Arkweid/lefthook

    8,434Auf GitHub ansehen↗

    Lefthook ist ein Git-Hook-Manager und Workflow-Automatisierer, der einen konfigurationsgesteuerten Ansatz verwendet, um Skripte zu verwalten, die durch Versionskontrollereignisse ausgelöst werden. Es fungiert als paralleler Task-Runner, der mehrere Skripte gleichzeitig ausführt, um die für Pre-Commit- oder Pre-Push-Prüfungen erforderliche Zeit zu reduzieren. Das Projekt bietet einen containerisierten Hook-Runner, um konsistente Abhängigkeiten und Toolsets auf verschiedenen Entwicklerrechnern sicherzustellen. Es unterstützt zudem die Monorepo-Orchestrierung durch die Ausführung von Skripten in spezifischen Unterverzeichnissen und die Verwaltung komplexer Projektstrukturen. Das System umfasst Funktionen für musterbasiertes Dateifiltern, um Qualitätssicherungsaufgaben nur auf geänderte Assets anzuwenden. Es unterstützt zudem die manuelle Aufgabenausführung, das Tagging und Gruppieren von Befehlen sowie lokale Konfigurations-Overrides für umgebungsspezifische Einstellungen.

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

    Go
    Auf GitHub ansehen↗8,434
  • crazyguitar/pysheeetAvatar von crazyguitar

    crazyguitar/pysheeet

    8,150Auf GitHub ansehen↗

    pysheeet ist eine technische Referenzbibliothek, die eine kuratierte Sammlung von Code-Snippets und Implementierungsmustern für fortgeschrittene Python-Entwicklung, Systemintegration und High-Performance-Computing bereitstellt. Sie dient als umfassender Leitfaden für die Implementierung von Low-Level-Netzwerkprogrammierung, nativen C-Erweiterungen sowie asynchroner und nebenläufiger Programmierung. Das Projekt bietet spezialisierte Frameworks für die Entwicklung und Bereitstellung von Large Language Models, einschließlich Werkzeugen für verteilte GPU-Inferenz und High-Performance-Serving. Es enthält zudem detaillierte Muster für die Orchestrierung von High-Performance-Computing-Clustern, die GPU-Ressourcenzuweisung und Multi-Node-Workload-Management abdecken. Die Bibliothek deckt ein breites Spektrum an Funktionen ab, einschließlich sicherer Netzwerkkommunikation und Kryptografie, Object-Relational-Mapping und Datenbankverwaltung sowie die Implementierung komplexer Datenstrukturen und Algorithmen. Sie bietet zudem Utilities für Speicherverwaltung, native Interoperabilität via Foreign-Function-Interfaces und systemnahe OS-Integration.

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

    Python
    Auf GitHub ansehen↗8,150
  • rust-lang/rust-by-exampleAvatar von rust-lang

    rust-lang/rust-by-example

    8,026Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗8,026
  • codebasics/pyAvatar von codebasics

    codebasics/py

    7,262Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗7,262
  • hyperf/hyperfAvatar von hyperf

    hyperf/hyperf

    6,855Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗6,855
  • uxlfoundation/onetbbAvatar von uxlfoundation

    uxlfoundation/oneTBB

    6,678Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗6,678
  • gevent/geventAvatar von gevent

    gevent/gevent

    6,440Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗6,440
  • dimitri/pgloaderAvatar von dimitri

    dimitri/pgloader

    6,295Auf GitHub ansehen↗

    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
    Auf GitHub ansehen↗6,295
  • balloonwj/cppguideAvatar von balloonwj

    balloonwj/CppGuide

    6,030Auf GitHub ansehen↗

    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.

    Auf GitHub ansehen↗6,030
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Unter-Tags erkunden

  • 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-TagsTraits 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-TagsCreating 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-TagDistributing 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.