Awesome GitHub RepositoriesGraph Computation

Angel is a distributed machine learning framework and graph computation engine designed to train predictive models and execute algorithms across a cluster of servers. It functions as a distributed parameter server that synchronizes model weights and gradients across multiple machines to handle massive datasets. The system provides a production environment for model inference deployment to provide real-time predictions for end users. It integrates with Spark to run machine learning workflows and data processing pipelines through a compatible interface. The framework covers distributed graph c

graph_nets 是一个图结构深度学习框架和库，用于构建消息传递神经网络。它提供了用于设计架构的工具，这些架构在节点和边上运行，以使用 TensorFlow 处理和推理图结构数据。 该框架实现了用于节点间迭代信息交换的消息传递范式。这种方法使得开发能够推理复杂图结构输入的模型成为可能，适用于路径查找和排序等任务，或作为物理系统未来状态和轨迹的预测器。

Titan is a distributed graph database and computing engine designed for storing and querying massive datasets of interconnected nodes and edges across multi-machine clusters. It functions as a scalable graph storage layer and transactional store, providing a framework for executing large-scale graph processing jobs and deep traversals. The system is distinguished by its pluggable storage backend, which decouples the graph engine from the physical persistence layer. It utilizes vertex-cut data partitioning to balance processing loads and a set-cardinality property model that allows single prop