Jeff Rasley
Jeff Rasley
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Cited by
Cited by
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
Bloom: A 176b-parameter open-access multilingual language model
TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
arXiv preprint arXiv:2211.05100, 2022
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
Planck: millisecond-scale monitoring and control for commodity networks
J Rasley, B Stephens, C Dixon, E Rozner, W Felter, K Agarwal, J Carter, ...
Proceedings of the 2014 ACM conference on SIGCOMM, 407-418, 2014
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
Efficient queue management for cluster scheduling
J Rasley, K Karanasos, S Kandula, R Fonseca, M Vojnovic, S Rao
Proceedings of the Eleventh European Conference on Computer Systems, 1-15, 2016
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
Retaining sandbox containment despite bugs in privileged memory-safe code
J Cappos, A Dadgar, J Rasley, J Samuel, I Beschastnikh, C Barsan, ...
Proceedings of the 17th ACM conference on Computer and communications …, 2010
Hyperdrive: Exploring hyperparameters with pop scheduling
J Rasley, Y He, F Yan, O Ruwase, R Fonseca
Proceedings of the 18th ACM/IFIP/USENIX Middleware Conference, 1-13, 2017
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
Crowdsourcing from scratch: A pragmatic experiment in data collection by novice requesters
A Papoutsaki, H Guo, D Metaxa-Kakavouli, C Gramazio, J Rasley, W Xie, ...
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 3 …, 2015
Wes Felter, Kanak Agarwal, John Carter, and Rodrigo Fonseca. 2014. Planck: Millisecond-scale Monitoring and Control for Commodity Networks
J Rasley, B Stephens, C Dixon, E Rozner
Proc. of SIGCOMM 10 (2619239.2626310), 0
Accelerating Large Scale Deep Learning Inference through {DeepCPU} at Microsoft
M Zhang, S Rajbandari, W Wang, E Zheng, O Ruwase, J Rasley, J Li, ...
2019 USENIX Conference on Operational Machine Learning (OpML 19), 5-7, 2019
Detecting latent cross-platform api violations
J Rasley, E Gessiou, T Ohmann, Y Brun, S Krishnamurthi, J Cappos
2015 IEEE 26th International Symposium on Software Reliability Engineering …, 2015
MCR-DL: Mix-and-Match Communication Runtime for Deep Learning
Q Anthony, AA Awan, J Rasley, Y He, A Shafi, M Abduljabbar, ...
arXiv preprint arXiv:2303.08374, 2023
Deepspeed inference: Enabling efficient inference of transformer models at unprecedented scale
R Yazdani Aminabadi, S Rajbhandari, M Zhang, AA Awan, C Li, D Li, ...
arXiv e-prints, arXiv: 2207.00032, 2022
DeepSpeed-Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales
Z Yao, RY Aminabadi, O Ruwase, S Rajbhandari, X Wu, AA Awan, ...
arXiv preprint arXiv:2308.01320, 2023
Seattle: The Internet as a Testbed
J Rasley, M Muhammad, A Hanson, S Morgan, A Loh, J Cappos
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