| Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity H Xia, Z Zheng, Y Li, D Zhuang, Z Zhou, X Qiu, Y Li, W Lin, SL Song Proceedings of the VLDB Endowment (VLDB 2024) 17 (2), 211 - 224, 2023 | 53 | 2023 |
| {Quant-LLM}: Accelerating the Serving of Large Language Models via {FP6-Centric}{Algorithm-System}{Co-Design} on Modern {GPUs} H Xia, Z Zheng, X Wu, S Chen, Z Yao, S Youn, A Bakhtiari, M Wyatt, ... 2024 USENIX Annual Technical Conference (USENIX ATC 24), 699-713, 2024 | 21* | 2024 |
| η-lstm: Co-designing highly-efficient large lstm training via exploiting memory-saving and architectural design opportunities X Zhang, H Xia, D Zhuang, H Sun, X Fu, MB Taylor, SL Song 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture …, 2021 | 17 | 2021 |
| Zeroquant (4+ 2): Redefining llms quantization with a new fp6-centric strategy for diverse generative tasks X Wu, H Xia, S Youn, Z Zheng, S Chen, A Bakhtiari, M Wyatt, ... arXiv preprint arXiv:2312.08583, 2023 | 12 | 2023 |
| Shift-BNN: Highly-efficient probabilistic Bayesian neural network training via memory-friendly pattern retrieving Q Wan, H Xia, X Zhang, L Wang, SL Song, X Fu MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture …, 2021 | 8 | 2021 |
| Enabling fast and memory-efficient acceleration for pattern matching workloads: the lightweight automata processing engine L Gong, C Wang, H Xia, X Chen, X Li, X Zhou IEEE Transactions on Computers 72 (4), 1011-1025, 2022 | 4 | 2022 |
| Lap: A lightweight automata processor for pattern matching tasks H Xia, L Gong, C Wang, X Chen, X Zhou 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 844-849, 2021 | 4 | 2021 |
| {MonoNN}: Enabling a New Monolithic Optimization Space for Neural Network Inference Tasks on Modern {GPU-Centric} Architectures D Zhuang, Z Zheng, H Xia, X Qiu, J Bai, W Lin, SL Song 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2024 | 3 | 2024 |
Shuaiwen Leon SongVP of Research, Together.ai; Ex-Microsoft; Tenured ProfessorE-mail megerősítve itt: together.ai