| 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 | 692 | 2019 |
| 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 | 536 | 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 | 487 | 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 | 362 | 2022 |
| SHiP: Signature-based hit predictor for high performance caching CJ Wu, A Jaleel, W Hasenplaugh, M Martonosi, SC Steely Jr, J Emer Proceedings of the 44th Annual IEEE/ACM International Symposium on …, 2011 | 335 | 2011 |
| 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 | 324 | 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 | 292 | 2020 |
| 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 | 261 | 2021 |
| MCM-GPU: Multi-chip-module GPUs for continued performance scalability A Arunkumar, E Bolotin, B Cho, U Milic, E Ebrahimi, O Villa, A Jaleel, ... ACM SIGARCH Computer Architecture News 45 (2), 320-332, 2017 | 244 | 2017 |
| 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 | 201 | 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 | 179 | 2020 |
| 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 | 166 | 2020 |
| PACMan: prefetch-aware cache management for high performance caching CJ Wu, A Jaleel, M Martonosi, SC Steely Jr, J Emer Proceedings of the 44th Annual IEEE/ACM International Symposium on …, 2011 | 159 | 2011 |
| CAWA: Coordinated warp scheduling and cache prioritization for critical warp acceleration of GPGPU workloads SY Lee, A Arunkumar, CJ Wu ACM SIGARCH Computer Architecture News 43 (3S), 515-527, 2015 | 114 | 2015 |
| Papaya: Practical, private, and scalable federated learning D Huba, J Nguyen, K Malik, R Zhu, M Rabbat, A Yousefpour, CJ Wu, ... Proceedings of Machine Learning and Systems 4, 814-832, 2022 | 112 | 2022 |
| 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 | 101 | 2022 |
| CAWS: Criticality-aware warp scheduling for GPGPU workloads SY Lee, CJ Wu Proceedings of the 23rd international conference on Parallel architectures …, 2014 | 99 | 2014 |
| 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 | 95 | 2021 |
| 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, 2024 | 93 | 2024 |
| 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 | 92 | 2021 |
