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Books and Theses
- 2021
[b1]Aurick Qiao:
Elastic Machine Learning Systems with Co-adaptation. Carnegie Mellon University, USA, 2021
Conference and Workshop Papers
- 2023
- [c6]Suhas Jayaram Subramanya
, Daiyaan Arfeen, Shouxu Lin, Aurick Qiao, Zhihao Jia, Gregory R. Ganger:
Sia: Heterogeneity-aware, goodput-optimized ML-cluster scheduling. SOSP 2023: 642-657 - 2021
- [c5]Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing:
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. OSDI 2021 - 2019
- [c4]Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric P. Xing:
Fault Tolerance in Iterative-Convergent Machine Learning. ICML 2019: 5220-5230 - 2018
- [c3]Aurick Qiao, Abutalib Aghayev, Weiren Yu, Haoyang Chen, Qirong Ho, Garth A. Gibson, Eric P. Xing:
Litz: Elastic Framework for High-Performance Distributed Machine Learning. USENIX ATC 2018: 631-644 - 2015
- [c2]Jinliang Wei, Wei Dai, Aurick Qiao, Qirong Ho, Henggang Cui, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Managed communication and consistency for fast data-parallel iterative analytics. SoCC 2015: 381-394 - 2014
- [c1]Shrinu Kushagra, Alejandro López-Ortiz, Aurick Qiao, J. Ian Munro:
Multi-Pivot Quicksort: Theory and Experiments. ALENEX 2014: 47-60
Informal and Other Publications
- 2024
- [i6]Yichao Fu, Siqi Zhu, Runlong Su, Aurick Qiao, Ion Stoica, Hao Zhang:
Efficient LLM Scheduling by Learning to Rank. CoRR abs/2408.15792 (2024) - [i5]Jaeseong Lee, Seung-won Hwang, Aurick Qiao, Daniel F. Campos, Zhewei Yao, Yuxiong He:
STUN: Structured-Then-Unstructured Pruning for Scalable MoE Pruning. CoRR abs/2409.06211 (2024) - [i4]Aurick Qiao, Zhewei Yao, Samyam Rajbhandari, Yuxiong He:
SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model Transformation. CoRR abs/2410.03960 (2024) - 2023
- [i3]Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Xuguang Ren, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Tim Baldwin, Eric P. Xing:
LLM360: Towards Fully Transparent Open-Source LLMs. CoRR abs/2312.06550 (2023) - 2020
- [i2]Aurick Qiao, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing:
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. CoRR abs/2008.12260 (2020) - 2018
- [i1]Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric P. Xing:
Fault Tolerance in Iterative-Convergent Machine Learning. CoRR abs/1810.07354 (2018)
Coauthor Index
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