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He Yuxiong
He Yuxiong
Microsoft Research
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Zero: Memory optimizations toward training trillion parameter models
S Rajbhandari, J Rasley, O Ruwase, Y He
SC20: International Conference for High Performance Computing, Networking …, 2020
10572020
Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
J Rasley, S Rajbhandari, O Ruwase, Y He
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
9792020
Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model
S Smith, M Patwary, B Norick, P LeGresley, S Rajbhandari, J Casper, ...
arXiv preprint arXiv:2201.11990, 2022
5972022
{Zero-offload}: Democratizing {billion-scale} model training
J Ren, S Rajbhandari, RY Aminabadi, O Ruwase, S Yang, M Zhang, D Li, ...
2021 USENIX Annual Technical Conference (USENIX ATC 21), 551-564, 2021
3272021
Graph query processing using plurality of engines
S Elnikety, Y He, S Sakr
US Patent 9,053,210, 2015
3072015
Zero-infinity: Breaking the gpu memory wall for extreme scale deep learning
S Rajbhandari, O Ruwase, J Rasley, S Smith, Y He
Proceedings of the international conference for high performance computing …, 2021
2872021
Zeroquant: Efficient and affordable post-training quantization for large-scale transformers
Z Yao, R Yazdani Aminabadi, M Zhang, X Wu, C Li, Y He
Advances in Neural Information Processing Systems 35, 27168-27183, 2022
2822022
Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale
RY Aminabadi, S Rajbhandari, AA Awan, C Li, D Li, E Zheng, O Ruwase, ...
SC22: International Conference for High Performance Computing, Networking …, 2022
2262022
Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation ai scale
S Rajbhandari, C Li, Z Yao, M Zhang, RY Aminabadi, AA Awan, J Rasley, ...
International conference on machine learning, 18332-18346, 2022
2002022
Provably-efficient job scheduling for energy and fairness in geographically distributed data centers
S Ren, Y He, F Xu
2012 IEEE 32nd International Conference on Distributed Computing Systems, 22-31, 2012
1562012
Learning intrinsic sparse structures within long short-term memory
W Wen, Y He, S Rajbhandari, M Zhang, W Wang, F Liu, B Hu, Y Chen, ...
arXiv preprint arXiv:1709.05027, 2017
1552017
The Cilkview scalability analyzer
Y He, CE Leiserson, WM Leiserson
Proceedings of the twenty-second annual ACM symposium on Parallelism in …, 2010
1462010
Adaptive work-stealing with parallelism feedback
K Agrawal, CE Leiserson, Y He, WJ Hsu
ACM Transactions on Computer Systems (TOCS) 26 (3), 1-32, 2008
1452008
Swayam: distributed autoscaling to meet slas of machine learning inference services with resource efficiency
A Gujarati, S Elnikety, Y He, KS McKinley, BB Brandenburg
Proceedings of the 18th ACM/IFIP/USENIX middleware conference, 109-120, 2017
1442017
Few-to-many: Incremental parallelism for reducing tail latency in interactive services
ME Haque, YH Eom, Y He, S Elnikety, R Bianchini, KS McKinley
ACM Sigplan Notices 50 (4), 161-175, 2015
1382015
{DeepCPU}: Serving {RNN-based} Deep Learning Models 10x Faster
M Zhang, S Rajbhandari, W Wang, Y He
2018 USENIX Annual Technical Conference (USENIX ATC 18), 951-965, 2018
1232018
Predictive parallelization: Taming tail latencies in web search
M Jeon, S Kim, S Hwang, Y He, S Elnikety, AL Cox, S Rixner
Proceedings of the 37th international ACM SIGIR conference on Research …, 2014
1212014
Performance modeling and scalability optimization of distributed deep learning systems
F Yan, O Ruwase, Y He, T Chilimbi
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
1142015
Accelerating training of transformer-based language models with progressive layer dropping
M Zhang, Y He
Advances in neural information processing systems 33, 14011-14023, 2020
1012020
Adaptive scheduling with parallelism feedback
K Agrawal, Y He, WJ Hsu, CE Leiserson
Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice …, 2006
912006
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