662 citations · 1.1k across the 11 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.LG2018★ 7 cited
Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training
Maohua Zhu, Jason Clemons, Jeff Pool +3
Exploiting sparsity enables hardware systems to run neural networks faster and more energy-efficiently. However, most prior sparsity-centric optimization techniques only accelerate…
cs.NE2018★ 1 cited
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip
Feiwen Zhu, Jeff Pool, Michael Andersch +2
Recurrent Neural Networks (RNNs) are powerful tools for solving sequence-based problems, but their efficacy and execution time are dependent on the size of the network. Following r…
cs.CV2018★ 47 cited
Efficient Sparse-Winograd Convolutional Neural Networks
Xingyu Liu, Jeff Pool, Song Han +1
Convolutional Neural Networks (CNNs) are computationally intensive, which limits their application on mobile devices. Their energy is dominated by the number of multiplies needed t…