| PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference A Ankit, IE Hajj, SR Chalamalasetti, G Ndu, M Foltin, RS Williams, ... Architecture Support for Programming Languages and Operating Systems (ASPLOS), 2019 | 609 | 2019 |
| Exploring neuromorphic computing based on spiking neural networks: Algorithms to hardware N Rathi, I Chakraborty, A Kosta, A Sengupta, A Ankit, P Panda, K Roy ACM Computing Surveys 55 (12), 1-49, 2023 | 297 | 2023 |
| Incremental learning in deep convolutional neural networks using partial network sharing SS Sarwar, A Ankit, K Roy Ieee Access 8, 4615-4628, 2019 | 177 | 2019 |
| Resparc: A reconfigurable and energy-efficient architecture with memristive crossbars for deep spiking neural networks A Ankit, A Sengupta, P Panda, K Roy Proceedings of the 54th Annual Design Automation Conference 2017, 27, 2017 | 150 | 2017 |
| Resistive crossbars as approximate hardware building blocks for machine learning: Opportunities and challenges I Chakraborty, M Ali, A Ankit, S Jain, S Roy, S Sridharan, A Agrawal, ... Proceedings of the IEEE 108 (12), 2276-2310, 2020 | 149 | 2020 |
| Xcel-RAM: Accelerating binary neural networks in high-throughput SRAM compute arrays A Agrawal, A Jaiswal, D Roy, B Han, G Srinivasan, A Ankit, K Roy IEEE Transactions on Circuits and Systems I: Regular Papers 66 (8), 3064-3076, 2019 | 147 | 2019 |
| An all-memristor deep spiking neural computing system: A step toward realizing the low-power stochastic brain P Wijesinghe, A Ankit, A Sengupta, K Roy IEEE Transactions on Emerging Topics in Computational Intelligence 2 (5 …, 2018 | 133 | 2018 |
| Panther: A programmable architecture for neural network training harnessing energy-efficient reram A Ankit, I El Hajj, SR Chalamalasetti, S Agarwal, M Marinella, M Foltin, ... IEEE Transactions on Computers 69 (8), 1128-1142, 2020 | 128 | 2020 |
| Geniex: A generalized approach to emulating non-ideality in memristive xbars using neural networks I Chakraborty, MF Ali, DE Kim, A Ankit, K Roy 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 121 | 2020 |
| In-memory computing in emerging memory technologies for machine learning: An overview K Roy, I Chakraborty, M Ali, A Ankit, A Agrawal 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 113 | 2020 |
| Energy-efficient neural computing with approximate multipliers SS Sarwar, S Venkataramani, A Ankit, A Raghunathan, K Roy ACM Journal on Emerging Technologies in Computing Systems (JETC) 14 (2), 1-23, 2018 | 93 | 2018 |
| Mixed precision quantization for ReRAM-based DNN inference accelerators S Huang, A Ankit, P Silveira, R Antunes, SR Chalamalasetti, I El Hajj, ... Proceedings of the 26th Asia and South Pacific Design Automation Conference …, 2021 | 73 | 2021 |
| Constructing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence I Chakraborty, D Roy, I Garg, A Ankit, K Roy Nature Machine Intelligence 2 (1), 43-55, 2020 | 69* | 2020 |
| TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system design A Ankit, A Sengupta, K Roy 2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 533-540, 2017 | 53 | 2017 |
| Hardware-software co-design for an analog-digital accelerator for machine learning J Ambrosi, A Ankit, R Antunes, SR Chalamalasetti, S Chatterjee, I El Hajj, ... 2018 IEEE International Conference on Rebooting Computing (ICRC), 1-13, 2018 | 50 | 2018 |
| Circuits and architectures for in-memory computing-based machine learning accelerators A Ankit, I Chakraborty, A Agrawal, M Ali, K Roy IEEE Micro 40 (6), 8-22, 2020 | 47 | 2020 |
| Pabo: Pseudo agent-based multi-objective bayesian hyperparameter optimization for efficient neural accelerator design M Parsa, A Ankit, A Ziabari, K Roy 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-8, 2019 | 43 | 2019 |
| Neural network accelerator design with resistive crossbars: Opportunities and challenges S Jain, A Ankit, I Chakraborty, T Gokmen, M Rasch, W Haensch, K Roy, ... IBM Journal of Research and Development 63 (6), 10: 1-10: 13, 2019 | 39 | 2019 |
| Space: Structured compression and sharing of representational space for continual learning G Saha, I Garg, A Ankit, K Roy IEEE Access 9, 150480-150494, 2021 | 36 | 2021 |
| A 35.5-127.2 tops/w dynamic sparsity-aware reconfigurable-precision compute-in-memory sram macro for machine learning M Ali, I Chakraborty, U Saxena, A Agrawal, A Ankit, K Roy IEEE Solid-State Circuits Letters 4, 129-132, 2021 | 35 | 2021 |
Kaushik RoyProfessor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
