Energy-precision tradeoffs in mobile Graphics Processing Units. - Jeff Pool; Anselmo Lastra; Montek Singh (ICCD, 2008)

An energy model for graphics processing units. - Jeff Pool; Anselmo Lastra; Montek Singh (ICCD, 2010)

Precision Selection for Energy-Effi cient Pixel Shaders. - Jeff Pool; Anselmo Lastra; Montek Singh (High Performance Graphics, 2011)

Power-Gated Arithmetic Circuits for Energy-Precision Tradeoffs in Mobile Graphics Processing Units. - Jeff Pool; Anselmo Lastra; Montek Singh (J. Low Power Electron., 2011)

Lossless compression of variable-precision floating-point buffers on GPUs. - Jeff Pool; Anselmo Lastra; Montek Singh (I3D, 2012)

Energy-precision tradeoffs in the graphics pipeline. - Jeff Pool (2012)

Learning both Weights and Connections for Efficient Neural Network. - Song Han 003; Jeff Pool; John Tran; William J. Dally (NIPS, 2015)

Learning both Weights and Connections for Efficient Neural Networks. - Song Han 003; Jeff Pool; John Tran; William J. Dally (CoRR, 2015)

DSD: Regularizing Deep Neural Networks with Dense-Sparse-Dense Training Flow. - Song Han 003; Jeff Pool; Sharan Narang; Huizi Mao; Shijian Tang; Erich Elsen; Bryan Catanzaro; John Tran; William J. Dally (CoRR, 2016)

Exploring the Granularity of Sparsity in Convolutional Neural Networks. - Huizi Mao; Song Han 003; Jeff Pool; Wenshuo Li; Xingyu Liu 001; Yu Wang 002; William J. Dally (CVPR Workshops, 2017)

DSD: Dense-Sparse-Dense Training for Deep Neural Networks. - Song Han 003; Jeff Pool; Sharan Narang; Huizi Mao; Enhao Gong; Shijian Tang; Erich Elsen; Peter Vajda; Manohar Paluri; John Tran; Bryan Catanzaro; William J. Dally (ICLR (Poster), 2017)

Exploring the Regularity of Sparse Structure in Convolutional Neural Networks. - Huizi Mao; Song Han 003; Jeff Pool; Wenshuo Li; Xingyu Liu 001; Yu Wang 002; William J. Dally (CoRR, 2017)

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks. - Minsoo Rhu; Mike O'Connor; Niladrish Chatterjee; Jeff Pool; Stephen W. Keckler (CoRR, 2017)

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks. - Minsoo Rhu; Mike O'Connor; Niladrish Chatterjee; Jeff Pool; Youngeun Kwon; Stephen W. Keckler (HPCA, 2018)

Efficient Sparse-Winograd Convolutional Neural Networks. - Xingyu Liu 001; Jeff Pool; Song Han 003; William J. Dally (ICLR (Poster), 2018)

Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip. - Feiwen Zhu; Jeff Pool; Michael Andersch; Jeremy Appleyard; Fung Xie (ICLR (Poster), 2018)

Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training. - Maohua Zhu; Jason Clemons; Jeff Pool; Minsoo Rhu; Stephen W. Keckler; Yuan Xie 001 (CoRR, 2018)

Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs. - Esha Choukse; Michael B. Sullivan 001; Mike O'Connor; Mattan Erez; Jeff Pool; David W. Nellans; Stephen W. Keckler (ISCA, 2020)

Self-Supervised Generative Adversarial Compression. - Chong Yu; Jeff Pool (NeurIPS, 2020)

Self-Supervised GAN Compression. - Chong Yu; Jeff Pool (CoRR, 2020)

Channel Permutations for N: M Sparsity. - Jeff Pool; Chong Yu (NeurIPS, 2021)

Accelerating Sparse Deep Neural Networks. - Asit K. Mishra; Jorge Albericio Latorre; Jeff Pool; Darko Stosic; Dusan Stosic; Ganesh Venkatesh; Chong Yu; Paulius Micikevicius (CoRR, 2021)

MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models. - Gongfan Fang; Hongxu Yin; Saurav Muralidharan; Greg Heinrich; Jeff Pool; Jan Kautz; Pavlo Molchanov 001; Xinchao Wang (NeurIPS, 2024)