| Throughput-optimized OpenCL-based FPGA accelerator for large-scale convolutional neural networks N Suda, V Chandra, G Dasika, A Mohanty, Y Ma, S Vrudhula, J Seo, ... Proceedings of the 2016 ACM/SIGDA international symposium on field …, 2016 | 721 | 2016 |
| XNOR-SRAM: In-memory computing SRAM macro for binary/ternary deep neural networks S Yin, Z Jiang, JS Seo, M Seok IEEE Journal of Solid-State Circuits 55 (6), 1733-1743, 2020 | 549 | 2020 |
| Optimizing loop operation and dataflow in FPGA acceleration of deep convolutional neural networks Y Ma, Y Cao, S Vrudhula, J Seo Proceedings of the 2017 ACM/SIGDA International Symposium on Field …, 2017 | 472 | 2017 |
| A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons J Seo, B Brezzo, Y Liu, BD Parker, SK Esser, RK Montoye, B Rajendran, ... 2011 IEEE Custom Integrated Circuits Conference (CICC), 1-4, 2011 | 465 | 2011 |
| Optimizing the convolution operation to accelerate deep neural networks on FPGA Y Ma, Y Cao, S Vrudhula, J Seo IEEE Transactions on Very Large Scale Integration (VLSI) Systems 26 (7 …, 2018 | 368 | 2018 |
| Large-scale neuromorphic spiking array processors: A quest to mimic the brain CS Thakur, JL Molin, G Cauwenberghs, G Indiveri, K Kumar, N Qiao, ... Frontiers in neuroscience 12, 891, 2018 | 296 | 2018 |
| Benchmarking tinyml systems: Challenges and direction CR Banbury, VJ Reddi, M Lam, W Fu, A Fazel, J Holleman, X Huang, ... arXiv preprint arXiv:2003.04821, 2020 | 285 | 2020 |
| Mitigating effects of non-ideal synaptic device characteristics for on-chip learning PY Chen, B Lin, IT Wang, TH Hou, J Ye, S Vrudhula, J Seo, Y Cao, S Yu 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 194-199, 2015 | 274 | 2015 |
| XNOR-RRAM: A scalable and parallel resistive synaptic architecture for binary neural networks X Sun, S Yin, X Peng, R Liu, J Seo, S Yu 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2018 | 253 | 2018 |
| C3SRAM: An in-memory-computing SRAM macro based on robust capacitive coupling computing mechanism Z Jiang, S Yin, JS Seo, M Seok IEEE Journal of Solid-State Circuits 55 (7), 1888-1897, 2020 | 252 | 2020 |
| Scalable and modularized RTL compilation of convolutional neural networks onto FPGA Y Ma, N Suda, Y Cao, J Seo, S Vrudhula 2016 26th international conference on field programmable logic and …, 2016 | 223 | 2016 |
| 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 | 195 | 2012 |
| An automatic RTL compiler for high-throughput FPGA implementation of diverse deep convolutional neural networks Y Ma, Y Cao, S Vrudhula, J Seo 2017 27th International Conference on Field Programmable Logic and …, 2017 | 180 | 2017 |
| Fully parallel write/read in resistive synaptic array for accelerating on-chip learning L Gao, IT Wang, PY Chen, S Vrudhula, J Seo, Y Cao, TH Hou, S Yu Nanotechnology 26 (45), 455204, 2015 | 151 | 2015 |
| High-throughput in-memory computing for binary deep neural networks with monolithically integrated RRAM and 90-nm CMOS S Yin, X Sun, S Yu, J Seo IEEE Transactions on Electron Devices 67 (10), 4185-4192, 2020 | 143 | 2020 |
| ALAMO: FPGA acceleration of deep learning algorithms with a modularized RTL compiler Y Ma, N Suda, Y Cao, S Vrudhula, J Seo Integration 62, 14-23, 2018 | 122 | 2018 |
| Low-power, adaptive neuromorphic systems: Recent progress and future directions A Basu, J Acharya, T Karnik, H Liu, H Li, JS Seo, C Song IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8 (1), 6-27, 2018 | 121 | 2018 |
| Fully parallel RRAM synaptic array for implementing binary neural network with (+ 1,− 1) weights and (+ 1, 0) neurons X Sun, X Peng, PY Chen, R Liu, J Seo, S Yu 2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC), 574-579, 2018 | 111 | 2018 |
| Reconfigurable and customizable general-purpose circuits for neural networks BV Brezzo, L Chang, SK Esser, DJ Friedman, Y Liu, DS Modha, ... US Patent 8,856,055, 2014 | 111 | 2014 |
| Recent advances and future prospects for memristive materials, devices, and systems MK Song, JH Kang, X Zhang, W Ji, A Ascoli, I Messaris, AS Demirkol, ... ACS nano 17 (13), 11994-12039, 2023 | 107 | 2023 |
