3 repositorios
Coordinating 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.
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Bolts-Android es una biblioteca de desarrollo móvil para Android que proporciona un framework para deep-linking y un sistema para gestionar tareas asíncronas. Funciona como un kit de herramientas para analizar intents entrantes, resolver metadatos de URL y enrutar a los usuarios a contenido nativo específico dentro de una aplicación. La biblioteca incluye un gestor de tareas para coordinar operaciones paralelas en segundo plano y manejar la ejecución segura para hilos (thread-safe). Este sistema utiliza tareas encadenables, tokens de cancelación para detener procesos activos y enrutamiento para asegurar que los resultados regresen al hilo principal de la interfaz de usuario. El framework también cubre la resolución y monitoreo de deep-links, utilizando broadcast listeners para rastrear transmisiones de enlaces y conectar el comportamiento de navegación con herramientas de analítica externas. Además, proporciona utilidades para compartir estado mutable a través de ámbitos asíncronos.
Coordinates multiple parallel asynchronous operations, triggering a completion event only after every task finishes.
This project is a promise-based concurrency framework and asynchronous task library for Swift and Objective-C. It functions as a workflow orchestrator that uses monadic transformations to chain operations and propagate results through a state machine. The library specializes in transforming traditional completion-handler APIs into promise-based structures to enable sequential execution. It provides mechanisms for coordinating simultaneous background processes, including the ability to aggregate results from multiple tasks or synchronize operations through racing and waiting. The framework co
Manages complex synchronization by racing multiple operations or waiting for all parallel tasks to complete.
CUDA.jl provides a programming interface for executing custom kernels and performing parallel array computing directly on NVIDIA graphics hardware using the Julia language. It serves as a framework for compiling and scheduling user-defined functions across multiple processing cores, enabling high-performance data processing and task synchronization. The library distinguishes itself through a custom compiler backend that translates high-level language functions into hardware-specific machine code. It manages complex hardware interactions through asynchronous stream scheduling, unified memory m
Coordinates concurrent operations and device contexts to maintain data consistency during asynchronous processing.