Speed up the convolution of so many subgraphs

If a heterogeneous graph generates many subgraphs, and each subgraph requires independent graph convolution, how can we speed up the convolution of so many subgraphs?
At present, I cycle a graph to generate multiple subgraphs, and then convolute each subgraph. It takes a lot of time.

You could use dgl.batch to batch them into a bigger graph and then do computation on that big graph.

Later on you can split it back with dgl.unbatch, or using readout functions such as dgl.sum_nodes to get a representation for each individual graph.

Thank you for your reply.