| 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, ... Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 112 | 2022 |
| 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 | 91 | 2020 |
| Check-N-Run: A Checkpointing System for Training Deep Learning Recommendation Models A Eisenman, KK Matam, S Ingram, D Mudigere, R Krishnamoorthi, K Nair, ... Networked Systems Design and Implementation (NSDI '22 Spring) 19, 2021 | 71 | 2021 |
| M. khorashadi, P D Mudigere, Y Hao, J Huang, Z Jia, A Tulloch, S Sridharan, X Liu, ... Bhattacharya, P. Lapukhov, M. Naumov, L. Qiao, M. Smelyanskiy, B. Jia, and V …, 2021 | 48 | 2021 |
| High-performance, distributed training of large-scale deep learning recommendation models D Mudigere, Y Hao, J Huang, A Tulloch, S Sridharan, X Liu, M Ozdal, ... arXiv preprint arXiv:2104.05158, 2021 | 34 | 2021 |
| Xrbench: An extended reality (xr) machine learning benchmark suite for the metaverse H Kwon, K Nair, J Seo, J Yik, D Mohapatra, D Zhan, J Song, P Capak, ... Proceedings of Machine Learning and Systems 5, 1-20, 2023 | 30 | 2023 |
| Artificial neural network training using flexible floating point tensors K Nair, A Yang, B Morris US Patent App. 16/004,243, 2019 | 25 | 2019 |
| Mtia: First generation silicon targeting meta's recommendation systems A Firoozshahian, J Coburn, R Levenstein, R Nattoji, A Kamath, O Wu, ... Proceedings of the 50th Annual International Symposium on Computer …, 2023 | 23 | 2023 |
| Circuit and method for computing depthwise convolution K Nair, AU Diril, D Mudigere, EKA Zadeh, O Wu, Y Hao US Patent 11,138,292, 2021 | 20 | 2021 |
| Apparatuses and methods to accelerate matrix multiplication M Urbanski, BJ Hickmann, M Rotzin, K Nair, A Yang, BS Morris, ... US Patent App. 17/256,195, 2021 | 16 | 2021 |
| Supporting massive DLRM inference through software defined memory EK Ardestani, C Kim, SJ Lee, L Pan, J Axboe, V Rampersad, B Agrawal, ... 2022 IEEE 42nd International Conference on Distributed Computing Systems …, 2022 | 15 | 2022 |
| Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems. arXiv e-prints, art M Naumov, J Kim, D Mudigere, S Sridharan, X Wang, W Zhao, S Yilmaz, ... arXiv preprint arXiv:2003.09518, 11, 2020 | 12 | 2020 |
| Scalable distributed training of recommendation models: An astra-sim+ ns3 case-study with tcp/ip transport S Rashidi, P Shurpali, S Sridharan, N Hassani, D Mudigere, K Nair, ... 2020 IEEE Symposium on High-Performance Interconnects (HOTI), 33-42, 2020 | 10 | 2020 |
| High throughput matrix processor with support for concurrently processing multiple matrices KN Nair, O Wu, EKA Zadeh, AU Diril, TM Ulrich, Y Hao, R Komuravelli, ... US Patent 11,409,838, 2022 | 9 | 2022 |
| Mapping convolution to a partition channel convolution engine KN Nair, R Komuravelli, AU Diril, EKA Zadeh, Y Hao, M Schatz, TM Ulrich, ... US Patent 11,520,853, 2022 | 7 | 2022 |
| Learning to collide: Recommendation system model compression with learned hash functions B Ghaemmaghami, M Ozdal, R Komuravelli, D Korchev, D Mudigere, ... arXiv preprint arXiv:2203.15837, 2022 | 7 | 2022 |
| Mechanism to perform non-linear functions in a machine learning accelerator B Daga, K Nair, P Janedula, AB Srinivasan, B Pazhanimala, A Vengallur US Patent 11,640,537, 2023 | 6 | 2023 |
| Check-n-run: A checkpointing system for training recommendation models A Eisenman, KK Matam, S Ingram, D Mudigere, R Krishnamoorthi, ... arXiv preprint arXiv:2010.08679 5, 2020 | 6 | 2020 |
| Circuit and method for calculating non-linear functions of floating-point numbers AR Kadkol, K Nair US Patent 11,106,430, 2021 | 5 | 2021 |
| Systems and methods for reducing power consumption of convolution operations of artificial neural networks KN Nair, AU Diril, Y Hao, TM Ulrich, R Komuravelli, EKA Zadeh, M Schatz US Patent 11,599,181, 2023 | 4 | 2023 |
