| Prunetrain: fast neural network training by dynamic sparse model reconfiguration S Lym, E Choukse, S Zangeneh, W Wen, S Sanghavi, M Erez Proceedings of the International Conference for High Performance Computing …, 2019 | 90 | 2019 |
| Branchnet: A convolutional neural network to predict hard-to-predict branches S Zangeneh, S Pruett, S Lym, YN Patt 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture …, 2020 | 39 | 2020 |
| Prunetrain: Gradual structured pruning from scratch for faster neural network training S Lym, E Choukse, S Zangeneh, W Wen, M Erez, S Shanghavi arXiv preprint arXiv:1901.09290, 2019 | 17 | 2019 |
| Dynamically sizing the tage branch predictor S Pruett, S Zangeneh, A Fakhrzadehgan, B Lin, Y Patt 5th JILP Workshop on Computer Architecture Competitions (JWAC-5 …, 2016 | 11 | 2016 |
| Branch prediction with multilayer neural networks: The value of specialization S Zangeneh, S Pruett, Y Patt Machine Learning for Computer Architecture and Systems, 2020 | 4 | 2020 |
| Using Convolutionan Neural Networks to Improve Branch Prediction S Zangeneh Kamali | 2* | 2022 |
| BranchNet: Using Offline Deep Learning To Predict Hard-To-Predict Branches S Zangeneh, S Pruett, S Lym, YN Patt | | 2019 |
