| Federated learning with non-iid data Y Zhao, M Li, L Lai, N Suda, D Civin, V Chandra arXiv preprint arXiv:1806.00582, 2018 | 2601 | 2018 |
| Bit fusion: Bit-level dynamically composable architecture for accelerating deep neural network H Sharma, J Park, N Suda, L Lai, B Chau, JK Kim, V Chandra, ... 2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture …, 2018 | 587 | 2018 |
| Hello edge: Keyword spotting on microcontrollers Y Zhang, N Suda, L Lai, V Chandra arXiv preprint arXiv:1711.07128, 2017 | 510 | 2017 |
| Cmsis-nn: Efficient neural network kernels for arm cortex-m cpus L Lai, N Suda, V Chandra arXiv preprint arXiv:1801.06601, 2018 | 442 | 2018 |
| Multi-scale high-resolution vision transformer for semantic segmentation J Gu, H Kwon, D Wang, W Ye, M Li, YH Chen, L Lai, V Chandra, DZ Pan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 175 | 2022 |
| Co-exploration of neural architectures and heterogeneous asic accelerator designs targeting multiple tasks L Yang, Z Yan, M Li, H Kwon, L Lai, T Krishna, V Chandra, W Jiang, Y Shi 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 126 | 2020 |
| Deep convolutional neural network inference with floating-point weights and fixed-point activations L Lai, N Suda, V Chandra arXiv preprint arXiv:1703.03073, 2017 | 125 | 2017 |
| Heterogeneous dataflow accelerators for multi-DNN workloads H Kwon, L Lai, M Pellauer, T Krishna, YH Chen, V Chandra 2021 IEEE International Symposium on High-Performance Computer Architecture …, 2021 | 122 | 2021 |
| Federated learning with non-iid data. arXiv 2018 Y Zhao, M Li, L Lai, N Suda, D Civin, V Chandra arXiv preprint arXiv:1806.00582, 2018 | 85 | 2018 |
| Federated learning with non-iid data. arXiv Y Zhao, M Li, L Lai, N Suda, D Civin, V Chandra arXiv preprint arXiv:1806.00582 10, 2018 | 70 | 2018 |
| Federated learning with non-iid data (2018) Y Zhao, M Li, L Lai, N Suda, D Civin, V Chandra arXiv preprint arXiv:1806.00582, 1806 | 68 | 1806 |
| Enabling deep learning at the lot edge L Lai, N Suda 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-6, 2018 | 66 | 2018 |
| Device-and circuit-level variability caused by line edge roughness for sub-32-nm FinFET technologies G Leung, L Lai, P Gupta, CO Chui IEEE transactions on electron devices 59 (8), 2057-2063, 2012 | 58 | 2012 |
| SlackProbe: A low overhead in situ on-line timing slack monitoring methodology L Lai, V Chandra, R Aitken, P Gupta 2013 Design, Automation & Test in Europe Conference & Exhibition (DATE), 282-287, 2013 | 57 | 2013 |
| SenseHAR: a robust virtual activity sensor for smartphones and wearables JV Jeyakumar, L Lai, N Suda, M Srivastava Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 15-28, 2019 | 56 | 2019 |
| DDRO: A novel performance monitoring methodology based on design-dependent ring oscillators TB Chan, P Gupta, AB Kahng, L Lai Thirteenth International Symposium on Quality Electronic Design (ISQED), 633-640, 2012 | 55 | 2012 |
| Privynet: A flexible framework for privacy-preserving deep neural network training M Li, L Lai, N Suda, V Chandra, DZ Pan arXiv preprint arXiv:1709.06161, 2017 | 50 | 2017 |
| VarEMU: An emulation testbed for variability-aware software L Wanner, S Elmalaki, L Lai, P Gupta, M Srivastava 2013 International Conference on Hardware/Software Codesign and System …, 2013 | 45 | 2013 |
| SlackProbe: A Flexible and Efficient In Situ Timing Slack Monitoring Methodology L Lai, V Chandra, RC Aitken, P Gupta IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2014 | 40 | 2014 |
| Not all ops are created equal! L Lai, N Suda, V Chandra arXiv preprint arXiv:1801.04326, 2018 | 33 | 2018 |
Vikas ChandraReality Labs, Meta在 meta.com 的电子邮件经过验证
