Parallel Computing Framework
2.3k 2026-04-18

ChunelFeng/CGraph

A cross-platform, pure C++11 and Python DAG framework designed for building and orchestrating complex parallel computation pipelines without third-party dependencies.

Core Features

Directed Acyclic Graph (DAG) based task scheduling.
Pure C++11 with no third-party dependencies.
Cross-platform compatibility (MacOS, Linux, Windows, Android).
Python API support for pipeline construction.
Advanced scheduling features: dependency, parallel, aggregation, conditional, loop, pause, resume, timeout.

Quick Start

pip install pycgraph

Detailed Introduction

CGraph is a robust, cross-platform Directed Acyclic Graph (DAG) framework built entirely with C++11, offering a powerful solution for orchestrating complex parallel computations. It enables developers to define tasks as nodes and their relationships, allowing for efficient execution of dependent tasks sequentially and independent tasks concurrently. With support for advanced scheduling logic like conditional execution, loops, and timeout settings, CGraph simplifies the development of high-performance, scalable applications. Its pure C++ core ensures minimal overhead, while Python bindings extend its accessibility to a broader developer base.

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