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Can you elaborate what you mean by "edge weights to nodes, but used the same matrices"?


The network retains the same topology, and therefore the same matrix dimensions, but some elements are set to zero, removing their contribution.


Relevant excerpt from https://news.ycombinator.com/item?id=38656172

> ...if we meet the shape 512x512 (512 is a power of 2, therefore a very "round" number in computer science), then maybe some kernel will be very fast; but then on a 512x511matrix, the same kernel may need to add some padding first to transform it into a round 512x512 matrix with zeros at the end of each row. Adding those zeros means shifting all rows, which is a very costly operation.




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