The invention discloses an FPGA
routing congestion prediction method based on a heterogeneous graph neural network, and the method comprises the steps: obtaining a
netlist file in an
FPGA design process, extracting the
topological information of the file, and constructing a
netlist subgraph;
fPGA architecture information is obtained, and an architecture subgraph is constructed according to the architecture information; obtaining a
layout file in the
FPGA design process, extracting position information of each block in the file to construct a
spatial mapping edge, and projecting nodes in the
netlist sub-graph to the architecture sub-graph through the
spatial mapping edge to obtain an integrated heterogeneous graph; constructing a heterogeneous graph neural network matched with the heterogeneous graph, wherein the heterogeneous graph neural network comprises a feature initialization module, a
message passing module and a reading module; a
data set is constructed according to the heterogeneous graph to
train a heterogeneous graph neural network, and a neural
network structure search strategy is used to optimize a
message passing module; and inputting the heterogeneous graph into the heterogeneous graph neural network to obtain
routing congestion information. According to the method, the accuracy of the FPGA
routing congestion prediction result can be improved, the generalization ability is higher, and the time for reasoning, training and data preprocessing is shortened.