| Pin: building customized program analysis tools with dynamic instrumentation CK Luk, R Cohn, R Muth, H Patil, A Klauser, G Lowney, S Wallace, ... Acm sigplan notices 40 (6), 190-200, 2005 | 5922 | 2005 |
| Tensorflow lite micro: Embedded machine learning for tinyml systems R David, J Duke, A Jain, V Janapa Reddi, N Jeffries, J Li, N Kreeger, ... Proceedings of Machine Learning and Systems 3, 800-811, 2021 | 935 | 2021 |
| GPUWattch: Enabling energy optimizations in GPGPUs J Leng, T Hetherington, A ElTantawy, S Gilani, NS Kim, TM Aamodt, ... ACM SIGARCH Computer Architecture News 41 (3), 487-498, 2013 | 817 | 2013 |
| Deep reinforcement learning for cyber security TT Nguyen, VJ Reddi IEEE Transactions on Neural Networks and Learning Systems, 2019 | 792 | 2019 |
| Mlperf inference benchmark VJ Reddi, C Cheng, D Kanter, P Mattson, G Schmuelling, CJ Wu, ... 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture …, 2020 | 743 | 2020 |
| Mlperf training benchmark P Mattson, C Cheng, G Diamos, C Coleman, P Micikevicius, D Patterson, ... Proceedings of Machine Learning and Systems 2, 336-349, 2020 | 439 | 2020 |
| Benchmarking tinyml systems: Challenges and direction CR Banbury, VJ Reddi, M Lam, W Fu, A Fazel, J Holleman, X Huang, ... arXiv preprint arXiv:2003.04821, 2020 | 406 | 2020 |
| Micronets: Neural network architectures for deploying tinyml applications on commodity microcontrollers C Banbury, C Zhou, I Fedorov, R Matas, U Thakker, D Gope, ... Proceedings of machine learning and systems 3, 517-532, 2021 | 382 | 2021 |
| Mlperf tiny benchmark C Banbury, VJ Reddi, P Torelli, J Holleman, N Jeffries, C Kiraly, P Montino, ... arXiv preprint arXiv:2106.07597, 2021 | 357 | 2021 |
| A dynamic compilation framework for controlling microprocessor energy and performance Q Wu, VJ Reddi, Y Wu, J Lee, D Connors, D Brooks, M Martonosi, ... 38th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO'05 …, 2005 | 288 | 2005 |
| Web search using mobile cores: quantifying and mitigating the price of efficiency V Janapa Reddi, BC Lee, T Chilimbi, K Vaid ACM SIGARCH Computer Architecture News 38 (3), 314-325, 2010 | 267 | 2010 |
| MLPerf: An industry standard benchmark suite for machine learning performance P Mattson, VJ Reddi, C Cheng, C Coleman, G Diamos, D Kanter, ... IEEE Micro 40 (2), 8-16, 2020 | 257 | 2020 |
| Pin: a binary instrumentation tool for computer architecture research and education VJ Reddi, A Settle, DA Connors, RS Cohn Proceedings of the 2004 workshop on Computer architecture education: held in …, 2004 | 244 | 2004 |
| High-performance and energy-efficient mobile web browsing on big/little systems Y Zhu, VJ Reddi 2013 IEEE 19th International Symposium on High Performance Computer …, 2013 | 226 | 2013 |
| PLR: A software approach to transient fault tolerance for multicore architectures A Shye, J Blomstedt, T Moseley, VJ Reddi, DA Connors IEEE Transactions on Dependable and Secure Computing 6 (2), 135-148, 2008 | 225 | 2008 |
| Mobile CPU's rise to power: Quantifying the impact of generational mobile CPU design trends on performance, energy, and user satisfaction M Halpern, Y Zhu, VJ Reddi 2016 IEEE International Symposium on High Performance Computer Architecture …, 2016 | 212 | 2016 |
| Edge impulse: An mlops platform for tiny machine learning V Janapa Reddi, A Elium, S Hymel, D Tischler, D Situnayake, C Ward, ... Proceedings of Machine Learning and Systems 5, 254-268, 2023 | 206* | 2023 |
| Dataperf: Benchmarks for data-centric ai development M Mazumder, C Banbury, X Yao, B Karlaš, W Gaviria Rojas, S Diamos, ... Advances in Neural Information Processing Systems 36, 5320-5347, 2023 | 205 | 2023 |
| Federated benchmarking of medical artificial intelligence with MedPerf A Karargyris, R Umeton, MJ Sheller, A Aristizabal, J George, A Wuest, ... Nature machine intelligence 5 (7), 799-810, 2023 | 179 | 2023 |
| TinyML: Current progress, research challenges, and future roadmap M Shafique, T Theocharides, VJ Reddy, B Murmann 2021 58th ACM/IEEE Design Automation Conference (DAC), 1303-1306, 2021 | 170 | 2021 |
David BrooksHaley Family Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
