Jilong Xue
Jilong Xue
Microsoft Research
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{NeuGraph}: Parallel deep neural network computation on large graphs
L Ma, Z Yang, Y Miao, J Xue, M Wu, L Zhou, Y Dai
2019 USENIX Annual Technical Conference (USENIX ATC 19), 443-458, 2019
GraM: scaling graph computation to the trillions
M Wu, F Yang, J Xue, W Xiao, Y Miao, L Wei, H Lin, Y Dai, L Zhou
Proceedings of the Sixth ACM Symposium on Cloud Computing, 408-421, 2015
Retentive network: A successor to transformer for large language models
Y Sun, L Dong, S Huang, S Ma, Y Xia, J Xue, J Wang, F Wei
arXiv preprint arXiv:2307.08621, 2023
Rammer: Enabling holistic deep learning compiler optimizations with {rTasks}
L Ma, Z Xie, Z Yang, J Xue, Y Miao, W Cui, W Hu, F Yang, L Zhang, ...
14th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2020
VoteTrust: Leveraging Friend Invitation Graph to Defend against Social Network Sybils
J Xue, Z Yang, X Yang, X Wang, L Chen, Y Dai
The 32nd IEEE International Conference on Computer Communications( INFOCOM'2013), 0
Seraph: an efficient, low-cost system for concurrent graph processing
J Xue, Z Yang, Z Qu, S Hou, Y Dai
Proceedings of the 23rd international symposium on High-performance parallel …, 2014
Garaph: Efficient {GPU-accelerated} Graph Processing on a Single Machine with Balanced Replication
L Ma, Z Yang, H Chen, J Xue, Y Dai
2017 USENIX Annual Technical Conference (USENIX ATC 17), 195-207, 2017
{Tux²}: Distributed Graph Computation for Machine Learning
W Xiao, J Xue, Y Miao, Z Li, C Chen, M Wu, W Li, L Zhou
14th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2017
VoteTrust: Leveraging friend invitation graph to defend against social network sybils
Z Yang, J Xue, X Yang, X Wang, Y Dai
IEEE Transactions on dependable and secure computing 13 (4), 488-501, 2015
Fast distributed deep learning over rdma
J Xue, Y Miao, C Chen, M Wu, L Zhang, L Zhou
Proceedings of the Fourteenth EuroSys Conference 2019, 1-14, 2019
{ROLLER}: Fast and efficient tensor compilation for deep learning
H Zhu, R Wu, Y Diao, S Ke, H Li, C Zhang, J Xue, L Ma, Y Xia, W Cui, ...
16th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2022
Towards efficient large-scale graph neural network computing
L Ma, Z Yang, Y Miao, J Xue, M Wu, L Zhou, Y Dai
arXiv preprint arXiv:1810.08403, 2018
Processing concurrent graph analytics with decoupled computation model
J Xue, Z Yang, S Hou, Y Dai
IEEE Transactions on Computers 66 (5), 876-890, 2016
A topology construct and control model with small-world and scale-free concepts for heterogeneous sensor networks
L Liu, X Qi, J Xue, M Xie
International Journal of Distributed Sensor Networks 10 (3), 374251, 2014
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
S Ma, H Wang, L Ma, L Wang, W Wang, S Huang, L Dong, R Wang, J Xue, ...
arXiv preprint arXiv:2402.17764, 2024
Dense-to-sparse gate for mixture-of-experts
X Nie, S Cao, X Miao, L Ma, J Xue, Y Miao, Z Yang, Z Yang, CUI Bin
Flexmoe: Scaling large-scale sparse pre-trained model training via dynamic device placement
X Nie, X Miao, Z Wang, Z Yang, J Xue, L Ma, G Cao, B Cui
Proceedings of the ACM on Management of Data 1 (1), 1-19, 2023
Evomoe: An evolutional mixture-of-experts training framework via dense-to-sparse gate
X Nie, X Miao, S Cao, L Ma, Q Liu, J Xue, Y Miao, Y Liu, Z Yang, B Cui
arXiv preprint arXiv:2112.14397, 2021
When computing meets heterogeneous cluster: Workload assignment in graph computation
J Xue, Z Yang, S Hou, Y Dai
2015 IEEE International Conference on Big Data (Big Data), 154-163, 2015
Uncovering user interaction dynamics in online social networks
Z Yang, C Wilson, B Zhao, Y Dai
Proceedings of the International AAAI Conference on Web and Social Media 9 …, 2015
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