KungFu: Making Training in Distributed Machine Learning Adaptive L Mai, G Li, M Wagenländer, K Fertakis, AO Brabete, P Pietzuch 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2020 | 82 | 2020 |
Taming hyper-parameters in deep learning systems L Mai, A Koliousis, G Li, AO Brabete, P Pietzuch ACM SIGOPS Operating Systems Review 53 (1), 52-58, 2019 | 28 | 2019 |
ServerlessLLM: Low-latency serverless inference for large language models Y Fu, L Xue, Y Huang, AO Brabete, D Ustiugov, Y Patel, L Mai 18th USENIX Symposium on Operating Systems Design and Implementation, 135-153, 2024 | 12 | 2024 |
ServerlessLLM: Locality-Enhanced Serverless Inference for Large Language Models Y Fu, L Xue, Y Huang, AO Brabete, D Ustiugov, Y Patel, L Mai arXiv preprint arXiv:2401.14351, 2024 | 9 | 2024 |
{ServerlessLLM}:{Low-Latency} Serverless Inference for Large Language Models Y Fu, L Xue, Y Huang, AO Brabete, D Ustiugov, Y Patel, L Mai 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2024 | | 2024 |
Kungfu: A Novel Distributed Training System for TensorFlow using Flexible Synchronisation AO Brabete, P Pietzuch, D Tuncer | | 2019 |
Adaptive Distributed Training of Deep Learning Models L Mai, G Li, AO Brabete, A Koliousis, P Pietzuch | | |