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LiSu avatar LiSu commented on May 26, 2024

GraphScope基于分布式GNN训练框架graphlearn-for-pytorch (GLTorch)支持大规模分布式GNN训练。GLTorch在模型层和PyG兼容,支持将PyG GNN训练扩展到分布式大图。为了支持在大于机器可用内存大小的图上训练GNN,PyG引入了一套可插拔的Remote Backend机制,即通过FeatureStore 和 GraphStore等抽象,支持第三方图存储引擎和PyG的对接。其中FeatureStore允许用户利用存储在远程的节点/边特征,GraphStore允许用户利用存储在远程的图结构信息,两者结合支持基于远端存储的GNN训练扩展。本项目旨在通过实现基于Graphscope的PyG Remote Backend,更进一步简化GraphScope和PyG的对接方式,提供对PyG用户友好的基于GraphScope进行分布式GNN训练的产品使用体验。

产出:

  • 基于GLTorch当前架构,设计FeatureStore 和 GraphStore在GraphScope上的实现方案
  • 完成Remote Backend整体实现,在GraphScope上提供基于PyG Remote Backend的分布式训练示例

难度: 初级
技术要求:熟练使用Python语言,熟悉C++

from graphscope.

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