FA2: Fast, accurate autoscaling for serving deep learning inference with SLA guarantees K Razavi, M Luthra, B Koldehofe, M Mühlhäuser, L Wang 2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium …, 2022 | 13 | 2022 |
Operator as a service: Stateful serverless complex event processing M Luthra, S Hennig, K Razavi, L Wang, B Koldehofe 2020 IEEE International Conference on Big Data (Big Data), 1964-1973, 2020 | 8 | 2020 |
Reconciling high accuracy, cost-efficiency, and low latency of inference serving systems M Salmani, S Ghafouri, A Sanaee, K Razavi, M Mühlhäuser, J Doyle, ... Proceedings of the 3rd Workshop on Machine Learning and Systems, 78-86, 2023 | 6 | 2023 |
FA2: Fast, accurate autoscaling for serving deep learning inference with SLA guarantees. In 2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS) K Razavi, M Luthra, B Koldehofe, M Mühlhäuser, L Wang IEEE, 146ś159. https://doi. org/10.1109/RTAS54340, 2022 | 6 | 2022 |
Distributed DNN serving in the network data plane K Razavi, G Karlos, V Nigade, M Mühlhäuser, L Wang Proceedings of the 5th International Workshop on P4 in Europe, 67-70, 2022 | 5 | 2022 |
IPA: Inference Pipeline Adaptation to Achieve High Accuracy and Cost-Efficiency S Ghafouri, K Razavi, M Salmani, A Sanaee, T Lorido-Botran, L Wang, ... arXiv preprint arXiv:2308.12871, 2023 | 1 | 2023 |
Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling K Razavi, S Ghafouri, M Mühlhäuser, P Jamshidi, L Wang arXiv preprint arXiv:2404.00704, 2024 | | 2024 |