RadiX-Net: Structured Sparse Matrices for Deep Neural Networks — mentioned by michelpp

Thu, 02 Jan 2020 21:27:00 GMT

The members of the GraphBLAS forum have discussed this chip a couple of times. There's a lot of research on making deep neural networks more sparse, not just by pruning a dense matrix, but by starting with a sparse matrix structure de novo. Lincoln Laboratory's Dr. Jeremy Kepner has a good paper on Radix-Net mixed radix topologies that achieve good learning ability but with far fewer neurons and memory requirements. Cited in the paper was a network constructed with these techniques that simulated the size and sparsity of the human brain: https://arxiv.org/pdf/1905.00416.pdf It would be cool…

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RadiX-Net: Structured Sparse Matrices for Deep Neural Networks · HackerPapers discussions

RadiX-Net: Structured Sparse Matrices for Deep Neural Networks — mentioned by michelpp