Sam Ade Jacobs

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 21

Top Topics

Frequent Patterns

Neural Architecture

Motion Planning

Technical Report

Top Venues

Future Gener. Comput. Syst.

Publications

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 (2024)
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 (2024)
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)
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)
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)
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 (2023)
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 (2023)
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)
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 (2022)
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)
Zachariah Carmichael, Tim Moon, Sam Ade Jacobs
Learning Interpretable Models Through Multi-Objective Neural Architecture Search. CoRR (2021)
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) (2020)
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 (2019)
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 (2019)
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)
Ya Ju Fan, Jonathan E. Allen, Sam Ade Jacobs, Brian C. Van Essen
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency. CoRR (2019)
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 (2019)
Sam Ade Jacobs, Nikoli Dryden, Roger A. Pearce, Brian Van Essen
Towards Scalable Parallel Training of Deep Neural Networks. MLHPC@SC (2017)
Sam Ade Jacobs, Aldo Dagnino
Large-Scale Industrial Alarm Reduction and Critical Events Mining Using Graph Analytics on Spark. BigDataService (2016)
Nikoli Dryden, Tim Moon, Sam Ade Jacobs, Brian Van Essen
Communication Quantization for Data-Parallel Training of Deep Neural Networks. MLHPC@SC (2016)
Erika Sy, Sam Ade Jacobs, Aldo Dagnino, Yu Ding
Graph-based clustering for detecting frequent patterns in event log data. CASE (2016)
K. Eric Harper, Jiang Zheng, Sam Ade Jacobs, Aldo Dagnino, Anton Jansen, Thomas Goldschmidt, Adamantios Marinakis
Industrial Analytics Pipelines. BigDataService (2015)
Sam Ade Jacobs, Nancy M. Amato
The anatomy of a distributed motion planning roadmap. IROS (2014)
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)
Cesar Rodriguez, Jory Denny, Sam Ade Jacobs, Shawna L. Thomas, Nancy M. Amato
Blind RRT: A probabilistically complete distributed RRT. IROS (2013)
Sam Ade Jacobs, Nicholas Stradford, Cesar Rodriguez, Shawna L. Thomas, Nancy M. Amato
A scalable distributed RRT for motion planning. ICRA (2013)
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)
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)
Troy McMahon, Sam Ade Jacobs, Bryan Boyd, Lydia Tapia, Nancy M. Amato
Local randomization in neighbor selection improves PRM roadmap quality. IROS (2012)
Sam Ade Jacobs, Nancy M. Amato
ACM SRC poster: from days to seconds: scalable parallel algorithm for motion planning. SC Companion (2011)