| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 2794 | 2024 |
| 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 | 589 | 2019 |
| The llama 3 herd of models A Grattafiori, A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, ... arXiv e-prints, arXiv: 2407.21783, 2024 | 91 | 2024 |
| Compilergym: Robust, performant compiler optimization environments for ai research C Cummins, B Wasti, J Guo, B Cui, J Ansel, S Gomez, S Jain, J Liu, ... 2022 IEEE/ACM International Symposium on Code Generation and Optimization …, 2022 | 80 | 2022 |
| LayerSkip: Enabling early exit inference and self-speculative decoding M Elhoushi, A Shrivastava, D Liskovich, B Hosmer, B Wasti, L Lai, ... arXiv preprint arXiv:2404.16710, 2024 | 56 | 2024 |
| Enabling full body AR with Mask R-CNN2Go A Jindal, A Tulloch, B Sharma, B Wasti, F Yang, G Gkioxari, J Kim, ... | 9 | 2018 |
| Q-gym: An equality saturation framework for dnn inference exploiting weight repetition C Fu, H Huang, B Wasti, C Cummins, R Baghdadi, K Hazelwood, Y Tian, ... Proceedings of the International Conference on Parallel Architectures and …, 2022 | 6 | 2022 |
| Loopstack: a lightweight tensor algebra compiler stack B Wasti, JP Cambronero, B Steiner, H Leather, A Zlateski arXiv preprint arXiv:2205.00618, 2022 | 5 | 2022 |
| LoopStack: ML-friendly ML Compiler Stack B Wasti, D Grubisic, B Steiner, A Zlateski NeurIPS Workshops, ML For Systems, 0 | 2 | |
| LoopTune: Optimizing Tensor Computations with Reinforcement Learning D Grubisic, B Wasti, C Cummins, J Mellor-Crummey, A Zlateski arXiv preprint arXiv:2309.01825, 2023 | 1 | 2023 |
| Semisupervised Learning on Heterogeneous Graphs and its Applications to Facebook News Feed C Ju, J Li, B Wasti, S Guo arXiv preprint arXiv:1805.07479, 2018 | | 2018 |
| Community Infrastructure for Applying Reinforcement Learning to Compiler Optimizations C Cummins, B Wasti, J Guo, B Cui, J Ansel, S Gomez, S Jain, J Liu, ... | | |
