Deep learning with limited numerical precision S Gupta, A Agrawal, K Gopalakrishnan, P Narayanan International conference on machine learning, 1737-1746, 2015 | 2620 | 2015 |
Phase change memory technology GW Burr, MJ Breitwisch, M Franceschini, D Garetto, K Gopalakrishnan, ... Journal of Vacuum Science & Technology B: Microelectronics and Nanometer …, 2010 | 1268 | 2010 |
Overview of candidate device technologies for storage-class memory GW Burr, BN Kurdi, JC Scott, CH Lam, K Gopalakrishnan, RS Shenoy IBM Journal of Research and Development 52 (4.5), 449-464, 2008 | 1142 | 2008 |
Pact: Parameterized clipping activation for quantized neural networks J Choi, Z Wang, S Venkataramani, PIJ Chuang, V Srinivasan, ... arXiv preprint arXiv:1805.06085, 2018 | 1044 | 2018 |
Training deep neural networks with 8-bit floating point numbers N Wang, J Choi, D Brand, CY Chen, K Gopalakrishnan Advances in neural information processing systems 31, 2018 | 594 | 2018 |
I-MOS: A novel semiconductor device with a subthreshold slope lower than kT/q K Gopalakrishnan, PB Griffin, JD Plummer Digest. International Electron Devices Meeting,, 289-292, 2002 | 459 | 2002 |
Activation and diffusion studies of ion-implanted p and n dopants in germanium CO Chui, K Gopalakrishnan, PB Griffin, JD Plummer, KC Saraswat Applied physics letters 83 (16), 3275-3277, 2003 | 375 | 2003 |
Impact ionization MOS (I-MOS)-Part I: device and circuit simulations K Gopalakrishnan, PB Griffin, JD Plummer IEEE Transactions on electron devices 52 (1), 69-76, 2004 | 355 | 2004 |
Hybrid 8-bit floating point (HFP8) training and inference for deep neural networks X Sun, J Choi, CY Chen, N Wang, S Venkataramani, VV Srinivasan, X Cui, ... Advances in neural information processing systems 32, 2019 | 235 | 2019 |
Accurate and efficient 2-bit quantized neural networks J Choi, S Venkataramani, VV Srinivasan, K Gopalakrishnan, Z Wang, ... Proceedings of Machine Learning and Systems 1, 348-359, 2019 | 205 | 2019 |
Adacomp: Adaptive residual gradient compression for data-parallel distributed training CY Chen, J Choi, D Brand, A Agrawal, W Zhang, K Gopalakrishnan Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 199 | 2018 |
Ultra-low precision 4-bit training of deep neural networks X Sun, N Wang, CY Chen, J Ni, A Agrawal, X Cui, S Venkataramani, ... Advances in Neural Information Processing Systems 33, 1796-1807, 2020 | 195 | 2020 |
Nanoscale electronic synapses using phase change devices BL Jackson, B Rajendran, GS Corrado, M Breitwisch, GW Burr, R Cheek, ... ACM Journal on Emerging Technologies in Computing Systems (JETC) 9 (2), 1-20, 2013 | 195 | 2013 |
Specifications of nanoscale devices and circuits for neuromorphic computational systems B Rajendran, Y Liu, J Seo, K Gopalakrishnan, L Chang, DJ Friedman, ... IEEE Transactions on Electron Devices 60 (1), 246-253, 2012 | 194 | 2012 |
Impact ionization MOS (I-MOS)-part II: experimental results K Gopalakrishnan, R Woo, C Jungemann, PB Griffin, JD Plummer IEEE Transactions on Electron Devices 52 (1), 77-84, 2004 | 187 | 2004 |
Highly-scalable novel access device based on mixed ionic electronic conduction (MIEC) materials for high density phase change memory (PCM) arrays K Gopalakrishnan, RS Shenoy, CT Rettner, K Virwani, DS Bethune, ... 2010 Symposium on VLSI Technology, 205-206, 2010 | 158 | 2010 |
A scalable multi-TeraOPS deep learning processor core for AI trainina and inference B Fleischer, S Shukla, M Ziegler, J Silberman, J Oh, V Srinivasan, J Choi, ... 2018 IEEE symposium on VLSI circuits, 35-36, 2018 | 153 | 2018 |
Rectifying element for a crosspoint based memory array architecture K Gopalakrishnan US Patent 8,203,873, 2012 | 138 | 2012 |
Rectifying element for a crosspoint based memory array architecture K Gopalakrishnan US Patent 7,382,647, 2008 | 134 | 2008 |
Approximate computing: Challenges and opportunities A Agrawal, J Choi, K Gopalakrishnan, S Gupta, R Nair, J Oh, DA Prener, ... 2016 IEEE International Conference on Rebooting Computing (ICRC), 1-8, 2016 | 123 | 2016 |