Sam Ade Jacobs

33 papers A* 4A 5B 1C 1Journal 12Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Training Ultra Long Context Language Model with Fully Pipelined Distributed Transformer. MLSys Jinghan Yao, Sam Ade Jacobs, Masahiro Tanaka, Olatunji Ruwase, Hari Subramoni, Dhabaleswar K. Panda
2025	—	`conf`	Universal Checkpointing: A Flexible and Efficient Distributed Checkpointing System for Large-Scale DNN Training with Reconfigurable Parallelism. USENIX ATC Xinyu Lian, Sam Ade Jacobs, Lev Kurilenko, Masahiro Tanaka, Stas Bekman, Olatunji Ruwase, Minjia Zhang
2024	—	`conf`	System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. IPDPS (Workshops) Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminabadi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2024	A*	`conf`	System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. PODC Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminadabi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2024	J	`jnl`	Training Ultra Long Context Language Model with Fully Pipelined Distributed Transformer. CoRR Jinghan Yao, Sam Ade Jacobs, Masahiro Tanaka, Olatunji Ruwase, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda
2024	J	`jnl`	Universal Checkpointing: Efficient and Flexible Checkpointing for Large Scale Distributed Training. CoRR Xinyu Lian, Sam Ade Jacobs, Lev Kurilenko, Masahiro Tanaka, Stas Bekman, Olatunji Ruwase, Minjia Zhang
2024	A*	`conf`	ZeRO++: Extremely Efficient Collective Communication for Large Model Training. ICLR Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
2023	J	`jnl`	DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. CoRR Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
2023	J	`jnl`	ZeRO++: Extremely Efficient Collective Communication for Giant Model Training. CoRR Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Connor Holmes, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
2022	J	`jnl`	Enabling machine learning-ready HPC ensembles with Merlin. Future Gener. Comput. Syst. 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
2022	B	`conf`	Scalable Composition and Analysis Techniques for Massive Scientific Workflows. e-Science 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
2021	J	`jnl`	Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models. Int. J. High Perform. Comput. Appl. 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
2021	J	`jnl`	Learning Interpretable Models Through Multi-Objective Neural Architecture Search. CoRR Zachariah Carmichael, Tim Moon, Sam Ade Jacobs
2020	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. 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
2019	J	`jnl`	Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency. CoRR Ya Ju Fan, Jonathan E. Allen, Sam Ade Jacobs, Brian C. Van Essen
2019	J	`jnl`	Merlin: Enabling Machine Learning-Ready HPC Ensembles. CoRR 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
2019	C	`conf`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER 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
2019	J	`jnl`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR 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
2019	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR 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
2017	—	`conf`	Towards Scalable Parallel Training of Deep Neural Networks. MLHPC@SC Sam Ade Jacobs, Nikoli Dryden, Roger A. Pearce, Brian Van Essen
2016	—	`conf`	Communication Quantization for Data-Parallel Training of Deep Neural Networks. MLHPC@SC Nikoli Dryden, Tim Moon, Sam Ade Jacobs, Brian Van Essen
2016	—	`conf`	Graph-based clustering for detecting frequent patterns in event log data. CASE Erika Sy, Sam Ade Jacobs, Aldo Dagnino, Yu Ding
2016	—	`conf`	Large-Scale Industrial Alarm Reduction and Critical Events Mining Using Graph Analytics on Spark. BigDataService Sam Ade Jacobs, Aldo Dagnino
2016	—	`ed.`	Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18 - June 22, 2016 Robotics: Science and Systems David Hsu, Nancy M. Amato, Spring Berman, Sam Ade Jacobs
2015	—	`conf`	Industrial Analytics Pipelines. BigDataService K. Eric Harper, Jiang Zheng, Sam Ade Jacobs, Aldo Dagnino, Anton Jansen, Thomas Goldschmidt, Adamantios Marinakis
2014	A	`conf`	The anatomy of a distributed motion planning roadmap. IROS Sam Ade Jacobs, Nancy M. Amato
2014	A	`conf`	Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms. IPDPS Adam Fidel, Sam Ade Jacobs, Shishir Sharma, Nancy M. Amato, Lawrence Rauchwerger
2013	A*	`conf`	A scalable distributed RRT for motion planning. ICRA Sam Ade Jacobs, Nicholas Stradford, Cesar Rodriguez, Shawna L. Thomas, Nancy M. Amato
2013	A	`conf`	Adaptive neighbor connection for PRMs: A natural fit for heterogeneous environments and parallelism. IROS Chinwe Ekenna, Sam Ade Jacobs, Shawna L. Thomas, Nancy M. Amato
2013	A	`conf`	Blind RRT: A probabilistically complete distributed RRT. IROS Cesar Rodriguez, Jory Denny, Sam Ade Jacobs, Shawna L. Thomas, Nancy M. Amato
2012	A*	`conf`	A scalable method for parallelizing sampling-based motion planning algorithms. ICRA Sam Ade Jacobs, Kasra Manavi, Juan Burgos, Jory Denny, Shawna L. Thomas, Nancy M. Amato
2012	A	`conf`	Local randomization in neighbor selection improves PRM roadmap quality. IROS Troy McMahon, Sam Ade Jacobs, Bryan Boyd, Lydia Tapia, Nancy M. Amato
2011	—	`conf`	ACM SRC poster: from days to seconds: scalable parallel algorithm for motion planning. SC Companion Sam Ade Jacobs, Nancy M. Amato