| Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators B Reagen, P Whatmough, R Adolf, S Rama, H Lee, SK Lee, ... International Symposium on Computer Architecture (ISCA) 43, 267-278, 2016 | 776 | 2016 |
| Machine learning at facebook: Understanding inference at the edge CJ Wu, D Brooks, K Chen, D Chen, S Choudhury, M Dukhan, ... 2019 IEEE international symposium on high performance computer architecture …, 2019 | 583 | 2019 |
| Aladdin: A pre-rtl, power-performance accelerator simulator enabling large design space exploration of customized architectures YS Shao, B Reagen, GY Wei, D Brooks ACM SIGARCH Computer Architecture News 42 (3), 97-108, 2014 | 416 | 2014 |
| 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 | 369 | 2018 |
| MachSuite: Benchmarks for Accelerator Design and Customized Architectures B Reagen, R Adolf, YS Shao, D Wei, Gu-Yeon, Brooks IISWC, 2014 | 351 | 2014 |
| 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 | 344 | 2020 |
| 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 | 257 | 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 | 213 | 2020 |
| Fathom: Reference workloads for modern deep learning methods R Adolf, S Rama, B Reagen, GY Wei, D Brooks 2016 IEEE International Symposium on Workload Characterization (IISWC), 1-10, 2016 | 210 | 2016 |
| Cheetah: Optimizing and accelerating homomorphic encryption for private inference B Reagen, WS Choi, Y Ko, VT Lee, HHS Lee, GY Wei, D Brooks 2021 IEEE International Symposium on High-Performance Computer Architecture …, 2021 | 194* | 2021 |
| A case for efficient accelerator design space exploration via bayesian optimization B Reagen, JM Hernández-Lobato, R Adolf, M Gelbart, P Whatmough, ... 2017 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2017 | 114 | 2017 |
| Deepreduce: Relu reduction for fast private inference NK Jha, Z Ghodsi, S Garg, B Reagen International Conference on Machine Learning, 4839-4849, 2021 | 103 | 2021 |
| Cryptonas: Private inference on a relu budget Z Ghodsi, AK Veldanda, B Reagen, S Garg Advances in Neural Information Processing Systems 33, 16961-16971, 2020 | 95 | 2020 |
| 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 | 67 | 2019 |
| The aladdin approach to accelerator design and modeling YS Shao, B Reagen, GY Wei, D Brooks IEEE Micro 35 (3), 58-70, 2015 | 61 | 2015 |
| 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 | 58 | 2018 |
| Deep learning for computer architects B Reagen, R Adolf, P Whatmough, GY Wei, D Brooks, M Martonosi Morgan & Claypool, 2017 | 50 | 2017 |
| Porcupine: A synthesizing compiler for vectorized homomorphic encryption M Cowan, D Dangwal, A Alaghi, C Trippel, VT Lee, B Reagen Proceedings of the 42nd ACM SIGPLAN International Conference on Programming …, 2021 | 47 | 2021 |
| Selective network linearization for efficient private inference M Cho, A Joshi, B Reagen, S Garg, C Hegde International Conference on Machine Learning, 3947-3961, 2022 | 46 | 2022 |
| 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 | 45 | 2019 |
David BrooksHaley Family Professor of Computer Science, Harvard Universityeecs.harvard.edu의 이메일 확인됨
