| Deep learning recommendation model for personalization and recommendation systems M Naumov, D Mudigere, HJM Shi, J Huang, N Sundaraman, J Park, ... arXiv preprint arXiv:1906.00091, 2019 | 623 | 2019 |
| Ares: A framework for quantifying the resilience of deep neural networks B Reagen, U Gupta, L Pentecost, P Whatmough, SK Lee, N Mulholland, ... Proceedings of the 55th Annual Design Automation Conference, 1-6, 2018 | 322 | 2018 |
| 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 | 306 | 2020 |
| The architectural implications of facebook's dnn-based personalized recommendation U Gupta, CJ Wu, X Wang, M Naumov, B Reagen, D Brooks, B Cottel, ... 2020 IEEE International Symposium on High Performance Computer Architecture …, 2020 | 274 | 2020 |
| Sustainable ai: Environmental implications, challenges and opportunities CJ Wu, R Raghavendra, U Gupta, B Acun, N Ardalani, K Maeng, G Chang, ... Proceedings of Machine Learning and Systems 4, 795-813, 2022 | 252 | 2022 |
| Chasing carbon: The elusive environmental footprint of computing U Gupta, YG Kim, S Lee, J Tse, HHS Lee, GY Wei, D Brooks, CJ Wu 2021 IEEE International Symposium on High-Performance Computer Architecture …, 2021 | 218 | 2021 |
| Recnmp: Accelerating personalized recommendation with near-memory processing L Ke, U Gupta, BY Cho, D Brooks, V Chandra, U Diril, A Firoozshahian, ... 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture …, 2020 | 190 | 2020 |
| Deeprecsys: A system for optimizing end-to-end at-scale neural recommendation inference U Gupta, S Hsia, V Saraph, X Wang, B Reagen, GY Wei, HHS Lee, ... 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture …, 2020 | 168 | 2020 |
| Rosetta: A realistic high-level synthesis benchmark suite for software programmable FPGAs Y Zhou, U Gupta, S Dai, R Zhao, N Srivastava, H Jin, J Featherston, ... Proceedings of the 2018 ACM/SIGDA International Symposium on Field …, 2018 | 139 | 2018 |
| RecSSD: near data processing for solid state drive based recommendation inference M Wilkening, U Gupta, S Hsia, C Trippel, CJ Wu, D Brooks, GY Wei Proceedings of the 26th ACM International Conference on Architectural …, 2021 | 88 | 2021 |
| ACT: Designing sustainable computer systems with an architectural carbon modeling tool U Gupta, M Elgamal, G Hills, GY Wei, HHS Lee, D Brooks, CJ Wu Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 78 | 2022 |
| Carbon explorer: A holistic framework for designing carbon aware datacenters B Acun, B Lee, F Kazhamiaka, K Maeng, U Gupta, M Chakkaravarthy, ... Proceedings of the 28th ACM International Conference on Architectural …, 2023 | 68 | 2023 |
| Masr: A modular accelerator for sparse rnns U Gupta, B Reagen, L Pentecost, M Donato, T Tambe, AM Rush, GY Wei, ... 2019 28th International Conference on Parallel Architectures and Compilation …, 2019 | 60 | 2019 |
| Weightless: Lossy weight encoding for deep neural network compression B Reagan, U Gupta, B Adolf, M Mitzenmacher, A Rush, GY Wei, D Brooks International Conference on Machine Learning, 4324-4333, 2018 | 49 | 2018 |
| Maxnvm: Maximizing dnn storage density and inference efficiency with sparse encoding and error mitigation L Pentecost, M Donato, B Reagen, U Gupta, S Ma, GY Wei, D Brooks Proceedings of the 52Nd Annual IEEE/ACM International Symposium on …, 2019 | 41 | 2019 |
| Dynamic hazard resolution for pipelining irregular loops in high-level synthesis S Dai, R Zhao, G Liu, S Srinath, U Gupta, C Batten, Z Zhang Proceedings of the 2017 ACM/SIGDA International Symposium on Field …, 2017 | 38 | 2017 |
| A 16nm 25mm2 SoC with a 54.5x Flexibility-Efficiency Range from Dual-Core Arm Cortex-A53 to eFPGA and Cache-Coherent Accelerators PN Whatmough, SK Lee, M Donato, HC Hsueh, S Xi, U Gupta, ... 2019 Symposium on VLSI Circuits, C34-C35, 2019 | 37 | 2019 |
| On-chip deep neural network storage with multi-level eNVM M Donato, B Reagen, L Pentecost, U Gupta, D Brooks, GY Wei Proceedings of the 55th Annual Design Automation Conference, 1-6, 2018 | 37 | 2018 |
| Deep learning recommendation model for personalization and recommendation systems. CoRR abs/1906.00091 (2019) M Naumov, D Mudigere, HJM Shi, J Huang, N Sundaraman, J Park, ... URL: https://arxiv. org/abs/1906 91, 1906 | 35 | 1906 |
| Cross-stack workload characterization of deep recommendation systems S Hsia, U Gupta, M Wilkening, CJ Wu, GY Wei, D Brooks 2020 IEEE International Symposium on Workload Characterization (IISWC), 157-168, 2020 | 32 | 2020 |
