| MNSIM 2.0: A behavior-level modeling tool for memristor-based neuromorphic computing systems Z Zhu, H Sun, K Qiu, L Xia, G Krishnan, G Dai, D Niu, X Chen, XS Hu, ... Proceedings of the 2020 on Great Lakes Symposium on VLSI, 83-88, 2020 | 79 | 2020 |
| SIAM: Chiplet-based scalable in-memory acceleration with mesh for deep neural networks G Krishnan, SK Mandal, M Pannala, C Chakrabarti, JS Seo, UY Ogras, ... ACM Transactions on Embedded Computing Systems (TECS) 20 (5s), 1-24, 2021 | 53 | 2021 |
| Accurate inference with inaccurate rram devices: A joint algorithm-design solution G Charan, A Mohanty, X Du, G Krishnan, RV Joshi, Y Cao IEEE Journal on Exploratory Solid-State Computational Devices and Circuits 6 …, 2020 | 42 | 2020 |
| Interconnect-Aware Area and Energy Optimization for In-Memory Acceleration of DNNs G Krishnan, SK Mandal, C Chakrabarti, J Seo, UY Ogras, Y Cao IEEE Design and Test, 2020 | 40 | 2020 |
| Accurate Inference with Inaccurate RRAM Devices: Statistical Data, Model Transfer, and On-line Adaptation G Charan, J Hazra, K Beckmann, X Du, G Krishnan, R Joshi, N Cady, ... Design Automation Conference (DAC) 2020, 2020 | 39 | 2020 |
| A Latency-Optimized Reconfigurable NoC for In-Memory Acceleration of DNNs SK Mandal, G Krishnan, C Chakrabarti, J Seo, Y Cao, U Ogras IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 1-14, 2020 | 36 | 2020 |
| Spikesim: An end-to-end compute-in-memory hardware evaluation tool for benchmarking spiking neural networks A Moitra, A Bhattacharjee, R Kuang, G Krishnan, Y Cao, P Panda IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2023 | 23 | 2023 |
| Impact of On-Chip Interconnect on In-Memory Acceleration of Deep Neural Networks G Krishnan, SK Mandal, C Chakrabarti, J Seo, UY Ogras, Y Cao Journal on Emerging Technologies in Computing Systems, 2021 | 23 | 2021 |
| Hybrid RRAM/SRAM in-memory computing for robust DNN acceleration G Krishnan, Z Wang, I Yeo, L Yang, J Meng, M Liehr, RV Joshi, NC Cady, ... IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2022 | 17 | 2022 |
| COIN: Communication-Aware In-Memory Acceleration for Graph Convolutional Networks SK Mandal, G Krishnan, AA Goksoy, GR Nair, Y Cao, UY Ogras IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2022 | 17 | 2022 |
| Robust RRAM-based In-Memory Computing in Light of Model Stability G Krishnan, J Sun, J Hazra, X Du, M Liehr, Z Li, K Beckmann, RV Joshi, ... IEEE International Reliability Physics Symposium (IRPS), 2021 | 15 | 2021 |
| Big-Little Chiplets for In-Memory Acceleration of DNNs: A Scalable Heterogeneous Architecture G Krishnan, AA Goksoy, SK Mandal, Z Wang, C Chakrabarti, J Seo, ... IEEE International Conference On Computer Aided Design (ICCAD), 2022 | 14 | 2022 |
| Structural Pruning in Deep Neural Networks: A Small-World Approach G Krishnan, X Du, Y Cao https://arxiv.org/abs/1911.04453, 2019 | 13 | 2019 |
| Towards Efficient Neural Networks On-a-chip: Joint Hardware-Algorithm Approaches X Du, G Krishnan, A Mohanty, Z Li, G Charan, Y Cao 2019 China Semiconductor Technology International Conference (CSTIC), 2019 | 13 | 2019 |
| Ai computing in light of 2.5 d interconnect roadmap: Big-little chiplets for in-memory acceleration Z Wang, GR Nair, G Krishnan, SK Mandal, N Cherian, JS Seo, ... 2022 International Electron Devices Meeting (IEDM), 23.6. 1-23.6. 4, 2022 | 11 | 2022 |
| Exploring Model Stability of Deep Neural Networks for Reliable RRAM-based In-Memory Acceleration G Krishnan, J Sun, J Hazra, X Du, M Liehr, Z Li, K Beckmann, RV Joshi, ... IEEE Transactions on Computers, 2022 | 11 | 2022 |
| Small-world-based Structural Pruning for Efficient FPGA Inference of Deep Neural Networks G Krishnan, Y Ma, Y Cao 2020 15th IEEE International Conference on Solid-State and Integrated …, 2020 | 11 | 2020 |
| Interconnect-Centric Benchmarking of In-Memory Acceleration for DNNS G Krishnan, SK Mandal, C Chakrabarti, J Seo, UY Ogras, Y Cao China Semiconductor Technology International Conference (CSTIC), 2021 | 10 | 2021 |
| Digital-assisted analog in-memory computing with rram devices Z Wang, PS Nalla, G Krishnan, RV Joshi, NC Cady, D Fan, J Seo, Y Cao 2023 International VLSI Symposium on Technology, Systems and Applications …, 2023 | 7 | 2023 |
| System-Level Benchmarking of Chiplet-based IMC Architectures for Deep Neural Network Acceleration G Krishnan, SK Mandal, C Chakrabarti, J Seo, UY Ogras, Y Cao IEEE 14th International Conference on ASIC 2021, 2021 | 7 | 2021 |
Yu CaoProfessor, University of MinnesotaBestätigte E-Mail-Adresse bei umn.edu
