| Algorithm and hardware design of discrete-time spiking neural networks based on back propagation with binary activations S Yin, SK Venkataramanaiah, GK Chen, R Krishnamurthy, Y Cao, ... 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-5, 2017 | 75 | 2017 |
| FixyNN: Efficient hardware for mobile computer vision via transfer learning PN Whatmough, C Zhou, P Hansen, SK Venkataramanaiah, J Seo, ... arXiv preprint arXiv:1902.11128, 2019 | 73* | 2019 |
| Automatic compiler based FPGA accelerator for CNN training SK Venkataramanaiah, Y Ma, S Yin, E Nurvithadhi, A Dasu, Y Cao, J Seo 2019 29th International Conference on Field Programmable Logic and …, 2019 | 57 | 2019 |
| FPGA-based low-batch training accelerator for modern CNNs featuring high bandwidth memory SK Venkataramanaiah, HS Suh, S Yin, E Nurvitadhi, A Dasu, Y Cao, ... Proceedings of the 39th International Conference on Computer-Aided Design, 1-8, 2020 | 29 | 2020 |
| Fixyfpga: Efficient fpga accelerator for deep neural networks with high element-wise sparsity and without external memory access J Meng, SK Venkataramanaiah, C Zhou, P Hansen, P Whatmough, J Seo 2021 31st International Conference on Field-Programmable Logic and …, 2021 | 28 | 2021 |
| Deep neural network training accelerator designs in ASIC and FPGA SK Venkataramanaiah, S Yin, Y Cao, JS Seo 2020 International SoC Design Conference (ISOCC), 21-22, 2020 | 18 | 2020 |
| Minimizing area and energy of deep learning hardware design using collective low precision and structured compression S Yin, G Srivastava, SK Venkataramanaiah, C Chakrabarti, V Berisha, ... 2017 51st Asilomar Conference on Signals, Systems, and Computers, 1907-1911, 2017 | 13 | 2017 |
| Algorithm-hardware co-optimization for energy-efficient drone detection on resource-constrained fpga HS Suh, J Meng, T Nguyen, V Kumar, Y Cao, JS Seo ACM Transactions on Reconfigurable Technology and Systems 16 (2), 1-25, 2023 | 10 | 2023 |
| Efficient and Modularized Training on FPGA for Real-time Applications. SK Venkataramanaiah, X Du, Z Li, S Yin, Y Cao, J Seo IJCAI, 5237-5239, 2020 | 4 | 2020 |
| A 28nm 8-bit Floating-Point Tensor Core based CNN Training Processor with Dynamic Activation/Weight Sparsification SK Venkataramanaiah, J Meng, HS Suh, I Yeo, J Saikia, SK Cherupally, ... ESSCIRC 2022-IEEE 48th European Solid State Circuits Conference (ESSCIRC), 89-92, 2022 | 3 | 2022 |
| FP-IMC: A 28nm All-Digital Configurable Floating-Point In-Memory Computing Macro J Saikia, A Sridharan, I Yeo, S Venkataramanaiah, D Fan, JS Seo ESSCIRC 2023-IEEE 49th European Solid State Circuits Conference (ESSCIRC …, 2023 | 2 | 2023 |
| A 28-nm 8-bit Floating-Point Tensor Core-Based Programmable CNN Training Processor With Dynamic Structured Sparsity SK Venkataramanaiah, J Meng, HS Suh, I Yeo, J Saikia, SK Cherupally, ... IEEE Journal of Solid-State Circuits 58 (7), 1885-1897, 2023 | 2 | 2023 |
| Online knowledge acquisition with the selective inherited model X Du, SK Venkataramanaiah, Z Li, J Seo, F Liu, Y Cao 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 2 | 2020 |
| Efficient continual learning at the edge with progressive segmented training X Du, SK Venkataramanaiah, Z Li, HS Suh, S Yin, G Krishnan, F Liu, ... Neuromorphic Computing and Engineering 2 (4), 044006, 2022 | 1 | 2022 |
| Energy Efficient ASIC/FPGA Neural Network Accelerators SK venkataramanaiah https://keep.lib.asu.edu/items/171744, 2022 | | 2022 |
| Energy Efficient Hardware Design of Neural Networks SK Venkataramanaiah Arizona State University, 2018 | | 2018 |
Jae-sun SeoCornell Tech在 cornell.edu 的电子邮件经过验证
