| Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective K Hazelwood, S Bird, D Brooks, S Chintala, U Diril, D Dzhulgakov, ... High Performance Computer Architecture (HPCA), 2018 IEEE International …, 2018 | 473 | 2018 |
| 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 | 314 | 2019 |
| 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 | 263 | 2019 |
| 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 | 142 | 2020 |
| Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications J Park, M Naumov, P Basu, S Deng, A Kalaiah, D Khudia, J Law, P Malani, ... arXiv preprint arXiv:1811.09886, 2018 | 124 | 2018 |
| 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 | 76 | 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 | 73 | 2020 |
| XChange: A market-based approach to scalable dynamic multi-resource allocation in multicore architectures X Wang, JF Martínez 2015 IEEE 21st International Symposium on High Performance Computer …, 2015 | 59 | 2015 |
| SWAP: Effective fine-grain management of shared last-level caches with minimum hardware support X Wang, S Chen, J Setter, JF Martínez 2017 IEEE International Symposium on High Performance Computer Architecture …, 2017 | 52 | 2017 |
| Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems M Naumov, J Kim, D Mudigere, S Sridharan, X Wang, W Zhao, S Yilmaz, ... arXiv preprint arXiv:2003.09518, 2020 | 36 | 2020 |
| ReBudget: Trading Off Efficiency vs. Fairness in Market-Based Multicore Resource Allocation via Runtime Budget Reassignment X Wang, JF Martínez ACM SIGPLAN Notices 51 (4), 19-32, 2016 | 35 | 2016 |
| Understanding training efficiency of deep learning recommendation models at scale B Acun, M Murphy, X Wang, J Nie, CJ Wu, K Hazelwood 2021 IEEE International Symposium on High-Performance Computer Architecture …, 2021 | 27 | 2021 |
| Global built-in self-repair for 3D memories with redundancy sharing and parallel testing X Wang, D Vasudevan, HHS Lee 2011 IEEE International 3D Systems Integration Conference (3DIC), 2011 IEEE …, 2012 | 23 | 2012 |
| Exploiting parallelism opportunities with deep learning frameworks YE Wang, CJ Wu, X Wang, K Hazelwood, D Brooks ACM Transactions on Architecture and Code Optimization (TACO) 18 (1), 1-23, 2020 | 16 | 2020 |
| Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models D Mudigere, Y Hao, J Huang, Z Jia, A Tulloch, S Sridharan, X Liu, ... arXiv preprint arXiv:2104.05158, 2021 | 4 | 2021 |
| Scalable dynamic multi-resource allocation in multicore systems X Wang Cornell University, 2017 | | 2017 |
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