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Awesome GitHub RepositoriesConcurrent Thread Execution

Management of multiple execution paths using thread handles and hardware concurrency detection.

Distinct from Concurrent Execution Monitors: Shortlist contains monitors, limiters, or AI thread managers; this is core language-level thread spawning.

Explore 33 awesome GitHub repositories matching programming languages & runtimes · Concurrent Thread Execution. Refine with filters or upvote what's useful.

Awesome Concurrent Thread Execution GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • federico-busato/modern-cpp-programmingfederico-busato 的头像

    federico-busato/Modern-CPP-Programming

    15,808在 GitHub 上查看↗

    This project is a comprehensive educational resource and programming course covering C++ language semantics and features from C++03 through C++26. It provides structured tutorials and technical guides focused on modern C++ development. The material offers specialized instruction on template metaprogramming, including the use of type traits and compile-time computations. It features detailed guides on concurrency and parallelism for multi-core execution, as well as a reference for software design applying SOLID principles and RAII. Additionally, it covers build performance optimization to redu

    Guides the spawning and management of multiple execution paths using C++ thread handles.

    HTMLc-plus-pluscode-qualitycompilers
    在 GitHub 上查看↗15,808
  • geniusvjr/learningnotesGeniusVJR 的头像

    GeniusVJR/LearningNotes

    13,145在 GitHub 上查看↗

    LearningNotes 是一个技术知识库和工程学习指南,专注于 Android 框架内部原理、系统架构和移动性能优化。它作为分析 Android 引导序列、进程引导和系统服务初始化的参考。 该项目提供了关于移动性能的详细指南,包括减少内存占用、识别内存泄漏和优化图像解码的策略。它进一步涵盖了使用 AIDL 和 Binder 内核驱动程序的 Android 进程间通信,以及通过 MVVM 和 MVP 等模式将业务逻辑与用户界面解耦的软件架构手册。 除了移动开发外,该仓库还包括用于技术面试准备的计算机科学知识库,涵盖数据结构、算法和操作系统概念。它还具有 Git 版本控制的实用参考,详细介绍了仓库管理、同步和分支工作流。

    Details the transfer of task progress and completion notifications from background worker threads back to the main thread.

    在 GitHub 上查看↗13,145
  • a8m/golang-cheat-sheeta8m 的头像

    a8m/golang-cheat-sheet

    8,802在 GitHub 上查看↗

    This project is a Go language cheat sheet and technical reference designed for rapid lookup of syntax patterns and core language features. It serves as a concise programming guide to Go type systems, tokens, and standard programming constructs. The reference covers foundational areas of the language, including concurrency and parallelism through the use of channels and lightweight threads. It also details data modeling using structs and embedding, as well as the language's approach to explicit error handling via return values. Additional guidance is provided on Go application architecture an

    Offers guidance on implementing concurrent execution paths using goroutines and channels.

    cheat-sheetscheatsheetgo
    在 GitHub 上查看↗8,802
  • tencent/libcoTencent 的头像

    Tencent/libco

    8,684在 GitHub 上查看↗

    libco is a C++ coroutine library and user-space task orchestrator designed for cooperative multitasking and high-concurrency execution. It functions as a high-concurrency network framework and a synchronous-to-asynchronous wrapper that allows blocking system calls and socket functions to run asynchronously without modifying existing business logic. The project utilizes a specialized stack-copying context switching model to support millions of simultaneous TCP connections on a single machine. It includes a high-performance time wheel scheduler for managing asynchronous background jobs and dela

    Enables pausing and resuming multiple functions to handle high volumes of concurrent processing.

    C++
    在 GitHub 上查看↗8,684
  • jackzhenguo/python-small-examplesjackzhenguo 的头像

    jackzhenguo/python-small-examples

    8,132在 GitHub 上查看↗

    This project is a comprehensive library of practical Python code examples and patterns. It provides a collection of scripts and snippets designed to demonstrate a wide range of programming tasks, from basic syntax to advanced implementation patterns. The repository focuses on several core domains, including the implementation of concurrency and multithreading examples, data analysis snippets for cleaning and manipulating tabular data, and various data visualization examples. It also covers automation scripts for file system management and a variety of general programming patterns. Additional

    Manages concurrent tasks using shared-memory threads and locking mechanisms to handle synchronization.

    Pythondata-sciencemachine-learningpython
    在 GitHub 上查看↗8,132
  • gevent/geventgevent 的头像

    gevent/gevent

    6,440在 GitHub 上查看↗

    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

    Runs tasks in a dedicated thread pool that bypasses monkey-patching to maintain native OS thread compatibility.

    Pythonasynciocoroutinesgreenlet
    在 GitHub 上查看↗6,440
  • arthenica/ffmpeg-kitarthenica 的头像

    arthenica/ffmpeg-kit

    5,836在 GitHub 上查看↗

    ffmpeg-kit is a cross-platform SDK that wraps FFmpeg and FFprobe into native libraries for Android, iOS, macOS, Linux, and tvOS, enabling applications to execute media processing commands through platform-specific APIs. It provides a concurrent command executor that runs multiple FFmpeg operations simultaneously and collects results independently via thread-safe interfaces. The project includes a build system that compiles FFmpeg native libraries from source with configurable codec and library options for each target platform, and offers eight precompiled binary packages with different sets o

    Provides a concurrent command executor that runs multiple FFmpeg operations simultaneously.

    Candroidffmpegflutter
    在 GitHub 上查看↗5,836
  • angrave/systemprogrammingangrave 的头像

    angrave/SystemProgramming

    5,734在 GitHub 上查看↗

    This is an open-source, crowd-sourced wiki textbook that teaches Linux system programming in C. It covers the core operating system concepts of process management through the fork-exec-wait model, dynamic memory allocation using implicit free list heap allocators, inode-based file systems, inter-process communication via pipes and shared memory, POSIX threads with synchronization primitives, signal-based asynchronous notification, virtual memory with page table translation, and runtime diagnostics using Valgrind and GDB. The textbook distinguishes itself by providing practical, implementation

    Teaches concurrent thread execution within a single process, a fundamental system programming concept.

    在 GitHub 上查看↗5,734
  • njhu/iosprojectNJHu 的头像

    NJHu/iOSProject

    5,426在 GitHub 上查看↗

    该项目是 Objective-C iOS 应用程序演示和代码示例的集合。它提供了 iOS 环境中核心开发模式和系统级功能的实现。 该仓库专注于 Objective-C 运行时示例,演示了动态方法分发和运行时方法交换(swizzling)以修改对象行为。它还包括一个 Core Animation UI 库以及 iOS 多线程和并发管理的示例。 该项目涵盖了 UI 动画和图形、并发任务协调以及集成第三方服务进行身份验证和社交分享的功能。

    Manages multiple execution paths using thread management tools to keep the interface responsive.

    Objective-Canimationcoreanimationcoregraphics
    在 GitHub 上查看↗5,426
  • reactor/reactor-corereactor 的头像

    reactor/reactor-core

    5,224在 GitHub 上查看↗

    Reactor Core is a reactive programming toolkit and non-blocking foundation for composing asynchronous data pipelines on the JVM. It serves as an asynchronous stream processing framework and a backpressure management system, allowing developers to transform, filter, and combine sequences of events while regulating data flow between producers and consumers to prevent resource exhaustion. The library differentiates itself through a sophisticated concurrency scheduling system and demand-based flow control. It decouples signal processing from specific threads using a scheduler registry and provide

    Provides a comprehensive scheduler registry to manage thread execution and decouple signal processing from specific threads.

    Javaasynchronousflowflux
    在 GitHub 上查看↗5,224
  • giantray/stackoverflow-java-top-qagiantray 的头像

    giantray/stackoverflow-java-top-qa

    5,092在 GitHub 上查看↗

    本项目是一个全面的 Java 编程知识库和技术参考存储库。它提供了一个精选的提炼答案、API 文档和故障排除指南集合,旨在帮助开发者解决常见的编码挑战和语言陷阱。 该存储库的特色在于结构化的知识架构方法,利用以比较为中心的分析来突出不同库实现和语言特性之间的权衡。它将高影响力的社区讨论整理为标准化格式,按架构、并发和安全模式组织技术解决方案。 内容涵盖了广泛的技术领域,包括核心语言规范、并发管理、内存管理和软件设计模式。它还包括关于运行时故障排除、数据结构实现、反射与元数据以及 API 集成模式的指导。 该文档作为实现标准软件架构模式和解决环境配置问题的技术参考。

    Analyzes trade-offs between runnable interfaces and thread classes to determine the optimal concurrency strategy.

    在 GitHub 上查看↗5,092
  • lunatic-solutions/lunaticlunatic-solutions 的头像

    lunatic-solutions/lunatic

    4,867在 GitHub 上查看↗

    Lunatic 是一个 WebAssembly 运行时和并发进程管理器,实现了 Erlang 风格的轻量级并发和容错模型。它作为一个分布式 Actor 系统运行,其中隔离的进程通过跨链接节点网络的异步消息传递进行通信。 该系统利用 WebAssembly 沙箱环境来隔离内存并限制每个单独进程的系统调用权限。这种基于能力的安全模型确保进程被沙箱化,以安全地执行不受信任的代码。 该平台提供用于分层监控和失败进程自动重启的容错监督树。它使用抢占式工作窃取调度程序来执行数千个轻量级绿色线程,从而管理高并发工作负载。 该运行时支持分布式系统协调,通过跨不同物理机器集群节点,并处理 TCP 和 WebSocket 等协议的网络流量。

    Runs thousands of concurrent lightweight green threads with minimal memory overhead to handle massive simultaneous workloads.

    Rustactorsassemblyscripterlang
    在 GitHub 上查看↗4,867
  • attractivechaos/klibattractivechaos 的头像

    attractivechaos/klib

    4,679在 GitHub 上查看↗

    klib 是一个全面的 C 标准库扩展和数据结构工具包。它为独立的 C 应用程序提供了一套基础工具,涵盖内存管理、数据组织和通用实用函数。 该项目具备生物信息学序列分析的专项能力,包括解析 FASTA、FASTQ 和 Newick 格式,以及实现 Smith-Waterman 序列比对和隐马尔可夫模型(HMM)。它还包含用于数值计算和表达式求值的数学库,以及用于随机访问远程数据的轻量级 HTTP 和 FTP 客户端。 该工具包涵盖了广泛的高性能计算原语,包括多线程模型、线性时间后缀数组构建和优化排序算法。它实现了多种高效的数据索引结构,如开放寻址哈希表、B 树和侵入式 AVL 树,并由基于内存池的序列管理提供支持。 其他实用工具还包括 JSON 数据解析和命令行参数解析。

    Implements multi-threading models to enable parallel task processing and increase overall throughput.

    C
    在 GitHub 上查看↗4,679
  • borgo-lang/borgoborgo-lang 的头像

    borgo-lang/borgo

    4,640在 GitHub 上查看↗

    Borgo 是一种静态类型语言和编译器,可将高级语法转换为 Go 源代码。它作为转译器,旨在利用 Go 运行时,同时引入以代数数据类型和基于结果的错误处理为核心的类型系统。 该语言的特色在于用 Result 和 Option 类型替换了 Go 的多返回值,并使用专用运算符进行简洁的错误传播。它实现了具有穷尽模式匹配的求和类型,并提供了一个为现有 Go 包生成绑定的工具,自动将多值返回转换为这些更安全的类型包装器。 该系统包含用于并发编程的原语,利用类型化通道和后台任务来协调异步进程。其类型系统进一步支持结构化接口实现、自动集合类型推断以及用于在结构体上组织方法的实现块。

    Spawns lightweight goroutines to execute functions concurrently without blocking the main thread.

    Rustcompilergolangprogramming-language
    在 GitHub 上查看↗4,640
  • mozilla/rhinomozilla 的头像

    mozilla/rhino

    4,594在 GitHub 上查看↗

    Rhino 是一个基于 Java 的 JavaScript 引擎,实现了用于在 Java 虚拟机(JVM)内执行的 ECMAScript 兼容层。它作为一个嵌入式脚本引擎和脚本桥接器,允许将 JavaScript 代码集成并执行在 Java 应用中。 该项目通过将 Java 类和对象映射到 JavaScript 环境中,促进了跨语言的直接通信。这种集成使脚本能够通过专用的映射机制与内部系统服务和原生宿主对象进行交互。 该引擎通过将 JavaScript 编译为 Java 字节码来优化性能,并支持双模式执行模型以平衡启动时间和运行时速度。它包括跨语言数据序列化、XML 处理以及为并发任务管理隔离执行上下文的功能。 提供了一个交互式 Shell,用于逻辑的实时编辑和调试。

    Manages multiple execution paths using isolated contexts to ensure thread-safe operation on shared objects.

    JavaScript
    在 GitHub 上查看↗4,594
  • tingsongyu/pytorch-tutorial-2ndTingsongYu 的头像

    TingsongYu/PyTorch-Tutorial-2nd

    4,555在 GitHub 上查看↗

    这是一个关于使用 PyTorch 构建神经网络的综合教学资源和课程。它涵盖了深度学习的基本构建块,包括张量操作、自动微分以及模块化神经网络组件的构建。 该仓库是多个专业领域的参考指南。它提供了计算机视觉任务(如图像分类、目标检测和语义分割)的实现细节,以及涉及 Transformer、循环网络和生成模型的自然语言处理工作流。此外,它还包括生成式 AI 的参考资料,专门关注通过扩散模型和对抗网络进行图像合成。 材料延伸至模型优化和部署流水线。它涵盖了通过量化和将模型导出为 ONNX 和 TensorRT 等格式来减小模型大小并提高推理速度的技术。其他能力领域包括用于并行加载的数据工程、使用自定义指标的模型评估,以及开源大语言模型的部署。 该项目主要以一系列 Jupyter Notebook 的形式提供。

    Controls execution threads and operator ordering to tune the runtime performance of neural networks.

    Jupyter Notebookcomputer-visiondeepsortdiffusion-models
    在 GitHub 上查看↗4,555
  • puniverse/quasarpuniverse 的头像

    puniverse/quasar

    4,553在 GitHub 上查看↗

    Quasar 是一个 JVM 并发框架,实现了 Actor 模型和一个轻量级线程库。它提供隔离的执行单元,通过异步消息传递进行通信,以消除共享的可变状态。 该项目通过一个能够在多个集群节点上运行的分布式 Actor 系统脱颖而出,该系统具有位置透明的注册表和 Actor 状态迁移功能。它利用工作窃取(work-stealing)Fiber 调度器来管理数百万个轻量级线程,允许任务在非阻塞 I/O 操作期间挂起,而不会阻塞底层的系统线程。 该框架包含广泛的功能,包括用于容错恢复的监督层次结构和用于数据流同步的 CSP 风格通信通道。它还提供了通过 Future 和数据流变量协调任务的原语,以及用于监控 Fiber 健康状况和检测失控执行的工具。 该系统使用 Java 实现。

    Utilizes green-thread style fibers to minimize memory overhead compared to standard OS threads.

    Javaactorsconcurrencyfibers
    在 GitHub 上查看↗4,553
  • prodesire/python-guide-cnProdesire 的头像

    Prodesire/Python-Guide-CN

    4,432在 GitHub 上查看↗

    Python-Guide-CN is a Chinese translation of a comprehensive guide to idiomatic Python programming and software development. It serves as a curated programming tutorial and ecosystem reference, providing a structured path for learning Python syntax, standard libraries, and professional coding patterns. The project distinguishes itself by offering detailed instructions for setting up development environments across Windows, macOS, and Linux. It specifically focuses on the selection of interpreters and the management of virtual environments to ensure a consistent workspace. The guide covers a b

    Explains how to manage execution threads and use locks to prevent data races.

    Batchfile
    在 GitHub 上查看↗4,432
  • alexandru/scala-best-practicesalexandru 的头像

    alexandru/scala-best-practices

    4,352在 GitHub 上查看↗

    这是一个关于在 Scala 中编写简洁、地道且可维护代码的精选指南和手册合集。它作为 Scala 编码标准、函数式编程设计和企业软件架构的综合指南。 该仓库提供了具体的并发管理策略,包括 Actor、Future 和线程池模式,以确保线程安全。它还包含一份性能优化手册,专注于减少内存分配和管理垃圾回收压力,以提高运行时效率。 这些指南涵盖了广泛的功能,包括应用程序架构、类型安全错误处理以及不可变数据结构的使用。它还通过标准化的命名约定、模块化 Trait 设计以及背压(back-pressure)和需求信号的实现,解决了软件质量保证问题。

    Recommends passing thread-pool configurations as parameters to decouple execution contexts from the runtime environment.

    在 GitHub 上查看↗4,352
  • alibaba/dragonwell8alibaba 的头像

    alibaba/dragonwell8

    4,322在 GitHub 上查看↗

    该项目是一个针对高吞吐量分布式应用程序优化的 OpenJDK 发行版。它具有一个协程运行时引擎,用轻量级对称协程替换内核线程,以提高并发性并减少调度开销,同时保持标准的 Java 接口兼容性。 该运行时的特色在于多租户资源管理器和专门的网络提供程序。它实现了 CPU 和内存的资源隔离以防止跨租户干扰,并集成了远程直接内存访问 (RDMA) 以实现高吞吐量、低延迟的数据传输。 该系统涵盖了广泛的性能和诊断功能,包括用于启动加速的配置引导预热编译、动态堆内存回收,以及针对大数据处理和数值计算的专门优化。其可观测性套件包括飞行记录器事件流、堆转储分析和协程状态检查。 通过季度安全和维护更新提供长期支持,并为容器化环境提供部署工具。

    Implements lightweight execution units managed by the runtime rather than the operating system to enable massive concurrency.

    Java
    在 GitHub 上查看↗4,322
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探索子标签

  • Bytecode CloningDuplicating compiled bytecode to enable parallel execution of the same script across multiple threads. **Distinct from Concurrent Thread Execution:** Focuses on the mechanism of cloning bytecode for parallelism rather than general thread management
  • Concurrency Strategy ComparisonsComparative analysis of different threading implementations to determine optimal performance. **Distinct from Concurrent Thread Execution:** Focuses on the trade-off analysis between Runnable and Thread, not just the execution of threads.
  • Execution Context DecouplingDecoupling the logic of asynchronous tasks from their execution thread-pool through parameter injection. **Distinct from Concurrent Thread Execution:** Focuses on the architectural decoupling of execution contexts, whereas the parent is general concurrent thread execution.
  • Execution Context SwitchingMechanisms for transferring task control and data between different execution threads. **Distinct from Concurrent Thread Execution:** Specifically covers the transfer of progress notifications between worker threads and the main thread.
  • FFmpeg Command ExecutorsRuns multiple FFmpeg commands simultaneously and collects results independently via thread-safe APIs. **Distinct from Concurrent Thread Execution:** Distinct from Concurrent Thread Execution: specifically executes FFmpeg commands concurrently, not general thread management.
  • Green ThreadsLightweight execution units managed by a runtime rather than the operating system to enable massive concurrency. **Distinct from Concurrent Thread Execution:** Focuses specifically on lightweight 'green' threads with minimal memory overhead, rather than general hardware-backed concurrent thread execution
  • Inference Thread ManagementControl of execution threads and operator order specifically for tuning neural network runtime performance. **Distinct from Concurrent Thread Execution:** Focuses on tuning AI inference performance rather than general language-level concurrency or thread spawning.
  • Thread Isolation HazardsDemonstrations of race conditions and data corruption resulting from shared memory access in concurrent thread execution. **Distinct from Concurrent Thread Execution:** Distinct from Concurrent Thread Execution: focuses on the hazards of shared memory access within isolated threads rather than the management of thread handles.
  • Thread Joining OperationsBlocking the calling thread until a specified thread completes and optionally retrieving its return value. **Distinct from Concurrent Thread Execution:** Distinct from Concurrent Thread Execution: focuses on the join operation for thread completion, not general thread spawning or management.
  • Thread Synchronization CoordinationsSuspends and resumes threads using object monitors to manage concurrent resource access. **Distinct from Concurrent Thread Execution:** Distinct from Concurrent Thread Execution: focuses on the wait/notify coordination logic, not just concurrent execution.