Method and apparatus for employing graph neural network by using plurality of processors

A method for processing graphical data comprising:

• obtaining an input graph including a plurality of network components, where each of the plurality of network components include a plurality of nodes and a plurality of edges;
• segmenting the input graph into a first partial input graph and a second partial input graph;
• generating, using a first processor and a graph neural network (GNN), first network features based on the first partial input graph, wherein each of the first network features includes a connectivity relation between a first network component and an adjacent first network component among the plurality of network components in the input graph;
• generating, using a second processor and the GNN, second network features based on the second partial input graph, wherein each of the second network features includes a connectivity relation between a second network component and an adjacent second network component among the plurality of network components in the input graph;
• transmitting, among the first processor and the second processor, a network feature from the first partial input graph to an adjacent network feature in the second partial input graph to obtain an aggregated network feature;
• and
• updating, using the second processor and a second layer of the GNN, the second network features based on the aggregated network feature.

An electronic device comprising:

• a plurality of processors, wherein the plurality of processors is configured to:
• obtain an input graph including a plurality of network components, where each of the plurality of network components include a plurality of nodes and a plurality of edges as a plurality of components,
• segment the input graph into a plurality of partial input graphs, wherein the plurality of partial input graphs includes a first partial input graph and a second partial input graph,
• generate network features based on the plurality of partial input graphs, wherein each of the network features includes a connectivity relation between a network component and an adjacent network component among the plurality of network components in the input graph,
• transmit, among the plurality of processors, a network feature from the first partial input graph to an adjacent network feature in the second partial input graph to obtain an aggregated network feature, and
• update the network feature of the plurality of network components based on the aggregated network feature.