activity
20162022
most citedTensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference

80 citations · 136 across the 7 of their papers we have counts for

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Showing 2018Show all

2 papers · 1 filter

cs.NE2018★ 2 cited

Laconic Deep Learning Computing

Sayeh Sharify, Mostafa Mahmoud, Alberto Delmas Lascorz +2

We motivate a method for transparently identifying ineffectual computations in unmodified Deep Learning models and without affecting accuracy. Specifically, we show that if we deco…

cs.NE2018★ 18 cited

Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How

Alberto Delmas, Patrick Judd, Dylan Malone Stuart +5

We show that, during inference with Convolutional Neural Networks (CNNs), more than 2x to $8x ineffectual work can be exposed if instead of targeting those weights and activations…