341 citations · 485 across the 30 of their papers we have counts for
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cs.DC2023
VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores
Roberto L. Castro, Andrei Ivanov, Diego Andrade +3
The increasing success and scaling of Deep Learning models demands higher computational efficiency and power. Sparsification can lead to both smaller models as well as higher compu…
cs.DC2023
A Theory of I/O-Efficient Sparse Neural Network Inference
Niels Gleinig, Tal Ben-Nun, Torsten Hoefler
As the accuracy of machine learning models increases at a fast rate, so does their demand for energy and compute resources. On a low level, the major part of these resources is con…