| Energy-aware memory mapping for hybrid FRAM-SRAM MCUs in intermittently-powered IoT devices H Jayakumar, A Raha, JR Stevens, V Raghunathan ACM Transactions on Embedded Computing Systems (TECS) 16 (3), 1-23, 2017 | 55 | 2017 |
| X-MANN: A crossbar based architecture for memory augmented neural networks A Ranjan, S Jain, JR Stevens, D Das, B Kaul, A Raghunathan Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 41 | 2019 |
| Softermax: Hardware/Software Co-Design of an Efficient Softmax for Transformers JR Stevens, R Venkatesan, S Dai, B Khailany, A Raghunathan 2021 58th ACM/IEEE Design Automation Conference (DAC), 469-474, 2021 | 38 | 2021 |
| AxBA: An approximate bus architecture framework JR Stevens, A Ranjan, A Raghunathan 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-8, 2018 | 30 | 2018 |
| Manna: An Accelerator for Memory-Augmented Neural Networks JR Stevens, A Ranjan, D Das, B Kaul, A Raghunathan Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019 | 27 | 2019 |
| Gnnerator: A hardware/software framework for accelerating graph neural networks JR Stevens, D Das, S Avancha, B Kaul, A Raghunathan 2021 58th ACM/IEEE Design Automation Conference (DAC), 955-960, 2021 | 17 | 2021 |
| Efficient softmax computation JR Stevens, R Venkatesan, SH Dai, B Khailany US Patent App. 17/112,795, 2022 | 8 | 2022 |
| Efficient ensembles of graph neural networks A Nagarajan, JR Stevens, A Raghunathan Proceedings of the 59th ACM/IEEE Design Automation Conference, 187-192, 2022 | 7 | 2022 |
| X-Former: In-Memory Acceleration of Transformers S Sridharan, JR Stevens, K Roy, A Raghunathan IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2023 | 5 | 2023 |
| Optimizing Transformers with Approximate Computing for Faster, Smaller and more Accurate NLP Models A Nagarajan, S Sen, JR Stevens, A Raghunathan arXiv preprint arXiv:2010.03688, 2020 | 5 | 2020 |
| Emerging Neural Workloads and Their Impact on Hardware D Brooks, MM Frank, T Gokmen, U Gupta, XS Hu, S Jain, AF Laguna, ... 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2020 | 5 | 2020 |
| AxFormer: Accuracy-driven Approximation of Transformers for Faster, Smaller and more Accurate NLP Models A Nagarajan, S Sen, JR Stevens, A Raghunathan 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 3 | 2022 |
| Accelerating Emerging Neural Workloads JR Stevens Purdue University Graduate School, 2021 | | 2021 |
| Specialized Transformers: Faster, Smaller and more Accurate NLP Models A Nagarajan, S Sen, JR Stevens, A Raghunathan | | 2021 |
| ACCLIB: Accelerators as libraries JR Stevens, Y Du, V Kozhikkottu, A Raghunathan 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE), 245-248, 2018 | | 2018 |
| Purdue MicroBrewer: A Microcontroller Generator JR Stevens, J Skubic, E Colter, M Swabey, M Johnson RISC-V International Conference, 2017 | | 2017 |
| RISC-V Business: A Configurable, Extensible RISC-V Core J Skubic, JR Stevens, CY Tan, M Johnson, M Swabey RISC-V International Conference, 2017 | | 2017 |
| Demonstration of a Platform Architecture That Enables Ultra-Low Power IoT Applications J Stevens, H Jayakumar, V Raghunathan | | 2015 |
Anand RaghunathanProfessor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
