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Jeff Pool
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2020 – today
- 2021
- [c13]Jeff Pool, Chong Yu:
Channel Permutations for N: M Sparsity. NeurIPS 2021: 13316-13327 - [i10]Asit K. Mishra, Jorge Albericio Latorre, Jeff Pool, Darko Stosic, Dusan Stosic, Ganesh Venkatesh, Chong Yu, Paulius Micikevicius:
Accelerating Sparse Deep Neural Networks. CoRR abs/2104.08378 (2021) - 2020
- [c12]Esha Choukse, Michael B. Sullivan, Mike O'Connor
, Mattan Erez
, Jeff Pool, David W. Nellans, Stephen W. Keckler:
Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs. ISCA 2020: 926-939 - [c11]Chong Yu, Jeff Pool:
Self-Supervised Generative Adversarial Compression. NeurIPS 2020 - [i9]Chong Yu, Jeff Pool:
Self-Supervised GAN Compression. CoRR abs/2007.01491 (2020)
2010 – 2019
- 2019
- [i8]Esha Choukse, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David W. Nellans, Stephen W. Keckler:
Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs. CoRR abs/1903.02596 (2019) - 2018
- [c10]Minsoo Rhu, Mike O'Connor
, Niladrish Chatterjee, Jeff Pool, Youngeun Kwon, Stephen W. Keckler:
Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks. HPCA 2018: 78-91 - [c9]Xingyu Liu, Jeff Pool, Song Han, William J. Dally:
Efficient Sparse-Winograd Convolutional Neural Networks. ICLR (Poster) 2018 - [c8]Feiwen Zhu, Jeff Pool, Michael Andersch, Jeremy Appleyard, Fung Xie:
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip. ICLR (Poster) 2018 - [i7]Xingyu Liu, Jeff Pool, Song Han, William J. Dally:
Efficient Sparse-Winograd Convolutional Neural Networks. CoRR abs/1802.06367 (2018) - [i6]Feiwen Zhu, Jeff Pool, Michael Andersch, Jeremy Appleyard, Fung Xie:
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip. CoRR abs/1804.10223 (2018) - [i5]Maohua Zhu, Jason Clemons, Jeff Pool, Minsoo Rhu, Stephen W. Keckler, Yuan Xie:
Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training. CoRR abs/1806.00512 (2018) - 2017
- [c7]Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, William J. Dally:
Exploring the Granularity of Sparsity in Convolutional Neural Networks. CVPR Workshops 2017: 1927-1934 - [c6]Song Han, Jeff Pool, Sharan Narang, Huizi Mao, Enhao Gong, Shijian Tang, Erich Elsen, Peter Vajda, Manohar Paluri, John Tran, Bryan Catanzaro, William J. Dally:
DSD: Dense-Sparse-Dense Training for Deep Neural Networks. ICLR (Poster) 2017 - [i4]Minsoo Rhu, Mike O'Connor, Niladrish Chatterjee, Jeff Pool, Stephen W. Keckler:
Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks. CoRR abs/1705.01626 (2017) - [i3]Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, William J. Dally:
Exploring the Regularity of Sparse Structure in Convolutional Neural Networks. CoRR abs/1705.08922 (2017) - 2016
- [i2]Song Han, Jeff Pool, Sharan Narang, Huizi Mao, Shijian Tang, Erich Elsen, Bryan Catanzaro, John Tran, William J. Dally:
DSD: Regularizing Deep Neural Networks with Dense-Sparse-Dense Training Flow. CoRR abs/1607.04381 (2016) - 2015
- [c5]Song Han, Jeff Pool, John Tran, William J. Dally:
Learning both Weights and Connections for Efficient Neural Network. NIPS 2015: 1135-1143 - [i1]Song Han, Jeff Pool, John Tran, William J. Dally:
Learning both Weights and Connections for Efficient Neural Networks. CoRR abs/1506.02626 (2015) - 2012
- [c4]Jeff Pool, Anselmo Lastra, Montek Singh:
Lossless compression of variable-precision floating-point buffers on GPUs. I3D 2012: 47-54 - 2011
- [j1]Jeff Pool, Anselmo Lastra, Montek Singh:
Power-Gated Arithmetic Circuits for Energy-Precision Tradeoffs in Mobile Graphics Processing Units. J. Low Power Electron. 7(2): 148-162 (2011) - [c3]Jeff Pool, Anselmo Lastra, Montek Singh:
Precision Selection for Energy-Effi cient Pixel Shaders. High Performance Graphics 2011: 159-168 - 2010
- [c2]Jeff Pool, Anselmo Lastra, Montek Singh:
An energy model for graphics processing units. ICCD 2010: 409-416
2000 – 2009
- 2008
- [c1]Jeff Pool, Anselmo Lastra, Montek Singh:
Energy-precision tradeoffs in mobile Graphics Processing Units. ICCD 2008: 60-67
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