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ORCIDSam Ade Jacobs
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2020 – today
- 2024
[c20]Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He:
ZeRO++: Extremely Efficient Collective Communication for Large Model Training. ICLR 2024- [c19]Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminabadi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He:
System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. IPDPS (Workshops) 2024: 1206-1208 - [c18]Sam Ade Jacobs
, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminadabi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He:
System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. PODC 2024: 121-130 - [i10]Marah I Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Harkirat S. Behl, Alon Benhaim, Misha Bilenko, Johan Bjorck, Sébastien Bubeck, Martin Cai, Caio César Teodoro Mendes, Weizhu Chen, Vishrav Chaudhary, Parul Chopra, Allie Del Giorno, Gustavo de Rosa, Matthew Dixon, Ronen Eldan, Dan Iter, Amit Garg, Abhishek Goswami, Suriya Gunasekar, Emman Haider, Junheng Hao, Russell J. Hewett, Jamie Huynh, Mojan Javaheripi, Xin Jin, Piero Kauffmann, Nikos Karampatziakis, Dongwoo Kim, Mahoud Khademi, Lev Kurilenko, James R. Lee, Yin Tat Lee, Yuanzhi Li, Chen Liang, Weishung Liu, Eric Lin, Zeqi Lin, Piyush Madan, Arindam Mitra, Hardik Modi, Anh Nguyen, Brandon Norick, Barun Patra, Daniel Perez-Becker, Thomas Portet, Reid Pryzant, Heyang Qin, Marko Radmilac, Corby Rosset, Sambudha Roy, Olatunji Ruwase, Olli Saarikivi, Amin Saied, Adil Salim, Michael Santacroce, Shital Shah, Ning Shang, Hiteshi Sharma, Xia Song, Masahiro Tanaka, Xin Wang, Rachel Ward, Guanhua Wang, Philipp Witte, Michael Wyatt, Can Xu, Jiahang Xu, Sonali Yadav, Fan Yang, Ziyi Yang, Donghan Yu, Chengruidong Zhang, Cyril Zhang, Jianwen Zhang, Li Lyna Zhang, Yi Zhang, Yue Zhang, Yunan Zhang, Xiren Zhou:
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone. CoRR abs/2404.14219 (2024) - [i9]Xinyu Lian, Sam Ade Jacobs, Lev Kurilenko, Masahiro Tanaka, Stas Bekman, Olatunji Ruwase, Minjia Zhang:
Universal Checkpointing: Efficient and Flexible Checkpointing for Large Scale Distributed Training. CoRR abs/2406.18820 (2024) - [i8]Jinghan Yao, Sam Ade Jacobs, Masahiro Tanaka, Olatunji Ruwase, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
Training Ultra Long Context Language Model with Fully Pipelined Distributed Transformer. CoRR abs/2408.16978 (2024) - 2023
- [i7]Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Connor Holmes, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He:
ZeRO++: Extremely Efficient Collective Communication for Giant Model Training. CoRR abs/2306.10209 (2023) - [i6]Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He:
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. CoRR abs/2309.14509 (2023) - 2022
- [j3]J. Luc Peterson, Benjamin Bay, Joe Koning, Peter B. Robinson, Jessica Semler, Jeremy White, Rushil Anirudh, Kevin Athey, Peer-Timo Bremer, Francesco Di Natale, David Fox, Jim A. Gaffney, Sam Ade Jacobs, Bhavya Kailkhura, Bogdan Kustowski, Steve H. Langer, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom:
Enabling machine learning-ready HPC ensembles with Merlin. Future Gener. Comput. Syst. 131: 255-268 (2022) - [c17]Shehtab Zaman, Tim Moon, Tom Benson, Sam Adé Jacobs, Kenneth Chiu, Brian Van Essen:
Parallelizing Graph Neural Networks via Matrix Compaction for Edge-Conditioned Networks. CCGRID 2022: 386-395 - [c16]Dong H. Ahn, Xiaohua Zhang, Jeffrey Mast, Stephen Herbein, Francesco Di Natale, Dan Kirshner, Sam Ade Jacobs, Ian Karlin, Daniel J. Milroy, Bronis R. de Supinski, Brian Van Essen, Jonathan E. Allen, Felice C. Lightstone:
Scalable Composition and Analysis Techniques for Massive Scientific Workflows. e-Science 2022: 32-43 - 2021
- [j2]Sam Ade Jacobs, Tim Moon, Kevin McLoughlin, Derek Jones, David Hysom, Dong H. Ahn, John C. Gyllenhaal, Pythagoras Watson, Felice C. Lightstone, Jonathan E. Allen, Ian Karlin, Brian Van Essen:
Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models. Int. J. High Perform. Comput. Appl. 35(5) (2021) - [c15]Arpan Jain, Tim Moon, Tom Benson, Hari Subramoni, Sam Adé Jacobs, Dhabaleswar K. Panda, Brian Van Essen:
SUPER: SUb-Graph Parallelism for TransformERs. IPDPS 2021: 629-638 - [i5]Zachariah Carmichael, Tim Moon, Sam Ade Jacobs:
Learning Interpretable Models Through Multi-Objective Neural Architecture Search. CoRR abs/2112.08645 (2021) - 2020
- [j1]Shusen Liu, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom:
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. 26(1): 291-300 (2020)
2010 – 2019
- 2019
- [c14]Sam Ade Jacobs, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer:
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER 2019: 1-10 - [i4]Ya Ju Fan, Jonathan E. Allen, Sam Ade Jacobs, Brian C. Van Essen:
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency. CoRR abs/1901.11152 (2019) - [i3]Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer:
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR abs/1907.08325 (2019) - [i2]Sam Ade Jacobs, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears:
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR abs/1910.02270 (2019) - [i1]J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven H. Langer, Peter B. Robinson, Jessica Semler, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom:
Merlin: Enabling Machine Learning-Ready HPC Ensembles. CoRR abs/1912.02892 (2019) - 2017
- [c13]Sam Ade Jacobs, Nikoli Dryden, Roger A. Pearce, Brian Van Essen:
Towards Scalable Parallel Training of Deep Neural Networks. MLHPC@SC 2017: 5:1-5:9 - 2016
- [c12]Sam Ade Jacobs, Aldo Dagnino:
Large-Scale Industrial Alarm Reduction and Critical Events Mining Using Graph Analytics on Spark. BigDataService 2016: 66-71 - [c11]Erika Sy, Sam Ade Jacobs, Aldo Dagnino, Yu Ding:
Graph-based clustering for detecting frequent patterns in event log data. CASE 2016: 972-977 - [c10]Nikoli Dryden, Tim Moon, Sam Ade Jacobs, Brian Van Essen:
Communication Quantization for Data-Parallel Training of Deep Neural Networks. MLHPC@SC 2016: 1-8 - [e1]David Hsu, Nancy M. Amato, Spring Berman, Sam Ade Jacobs:
Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18 - June 22, 2016. 2016, ISBN 978-0-9923747-2-3 [contents] - 2015
- [c9]K. Eric Harper, Jiang Zheng, Sam Ade Jacobs, Aldo Dagnino, Anton Jansen, Thomas Goldschmidt, Adamantios Marinakis:
Industrial Analytics Pipelines. BigDataService 2015: 242-248 - 2014
- [c8]Adam Fidel, Sam Ade Jacobs, Shishir Sharma, Nancy M. Amato, Lawrence Rauchwerger:
Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms. IPDPS 2014: 573-582 - [c7]Sam Ade Jacobs, Nancy M. Amato:
The anatomy of a distributed motion planning roadmap. IROS 2014: 3019-3026 - 2013
- [c6]Sam Ade Jacobs, Nicholas Stradford, Cesar Rodriguez, Shawna L. Thomas, Nancy M. Amato:
A scalable distributed RRT for motion planning. ICRA 2013: 5088-5095 - [c5]Chinwe Ekenna, Sam Ade Jacobs, Shawna L. Thomas, Nancy M. Amato:
Adaptive neighbor connection for PRMs: A natural fit for heterogeneous environments and parallelism. IROS 2013: 1249-1256 - [c4]Cesar Rodriguez, Jory Denny, Sam Ade Jacobs, Shawna L. Thomas, Nancy M. Amato:
Blind RRT: A probabilistically complete distributed RRT. IROS 2013: 1758-1765 - 2012
- [c3]Sam Ade Jacobs, Kasra Manavi, Juan Burgos, Jory Denny, Shawna L. Thomas, Nancy M. Amato:
A scalable method for parallelizing sampling-based motion planning algorithms. ICRA 2012: 2529-2536 - [c2]Troy McMahon, Sam Ade Jacobs, Bryan Boyd, Lydia Tapia, Nancy M. Amato:
Local randomization in neighbor selection improves PRM roadmap quality. IROS 2012: 4441-4448 - 2011
- [c1]Sam Ade Jacobs, Nancy M. Amato:
ACM SRC poster: from days to seconds: scalable parallel algorithm for motion planning. SC Companion 2011: 109-110
Coauthor Index
aka: Brian C. Van Essen
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last updated on 2024-12-10 20:45 CET by the dblp team
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