1 个仓库
Awesome GitHub RepositoriesDistributed GPU
Executing large-scale graph computations across multiple GPUs to handle massive datasets.
Distinct from Graph Processing: Focuses on the hardware distribution of graph workloads rather than general graph algorithms.
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Awesome Distributed GPU GitHub Repositories
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- dmlc/dgl
dmlc/dgl
14,283在 GitHub 上查看DGL is a Python library for building and training graph neural networks. It functions as a graph message passing framework and a geometric deep learning tool, enabling the development of models that analyze graph-structured data. The library is designed for large-scale graph processing, utilizing distributed training and neighbor sampling to handle datasets with billions of edges. It provides specialized support for heterogeneous graph modeling, allowing for the representation of complex real-world entities with multiple node and edge types. Its capabilities cover a wide range of graph tasks
Distributes deep learning workloads across multiple graphics processors to process billion-sized graphs efficiently.
Pythondeep-learninggraph-neural-networks
