SpMM message passing CUDA support for coalesced COO graphs #617
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…ions for COO graphs
- Leave public adjacency_matrix interface uniform, always returning a sparse adjacency_matrix - Implement custom _adjacency_matrix for propagate copy_xj for CUDA COO graphs, converting to dense when more efficient
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This PR adds support for efficient CUDA message passing on coalesced
:coographs by exploiting SpMM. Performance is comparable to the case of:sparsegraphs.The changes introduced by this PR include:
__adjacency_matrixfunction, used during message passing, that efficiently constructs aCuSparseMatrixCOOfor a:coograph. This is leveraged bypropagateto implement message passing via SpMM.CuSparseMatrixCOOis computed incorrectly. The fix involves changingcoalesceto sort the:coograph representation by target instead of source.GraphNeuralNetworksandGNNlibto cover coalesced:coographs.