Sam Ade Jacobs

Computer Scientist, Microsoft

Joined

January 2021

Names

Sam Ade Jacobs (Preferred)

Emails

****@llnl.gov (Confirmed)

****@microsoft.com (Confirmed)

****@me.com (Confirmed)

Personal Links

Homepage

DBLP

ORCID

Career & Education History

Computer Scientist

Microsoft (microsoft.com)

2022 – Present

Advisors, Relations & Conflicts

No relations added

Expertise

deep learning

distributed and parallel neural networks training

neural architecture search

graph analytics

feature learning and extraction

2013 – Present

Publications

Training Ultra Long Context Language Model with Fully Pipelined Distributed Transformer
Jinghan Yao, Sam Ade Jacobs, Masahiro Tanaka, Olatunji Ruwase, Hari Subramoni, Dhabaleswar Panda
- MLSys 2025
- Readers: Everyone
ZeRO++: Extremely Efficient Collective Communication for Large Model Training
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
- ICLR 2024 poster
- Readers: Everyone
Learning Debuggable Models Through Multi-Objective NAS
Zachariah J Carmichael, Tim Moon, Sam Ade Jacobs
- Published: 16 May 2023, Last Modified: 05 Sept 2023
- AutoML 2023 Workshop
- Readers: Everyone
Enabling Rapid COVID-19 Small Molecule Drug Design Through Scalable Deep Learning of Generative Models
Sam Ade Jacobs, Brian Van Essen, Felice C Lightstone
- 18 Sept 2021
- OpenReview Archive Direct Upload
- Readers: Everyone
Learning Interpretable Models Through Multi-Objective Neural Architecture Search
Zachariah Carmichael, Tim Moon, Sam Ade Jacobs
- 2021 (modified: 22 Mar 2022)
- CoRR 2021
- Readers: Everyone
SUPER: SUb-Graph Parallelism for TransformERs
Arpan Jain, Tim Moon, Tom Benson, Hari Subramoni, Sam Adé Jacobs, Dhabaleswar K. Panda, Brian Van Essen
- 2021 (modified: 22 Mar 2022)
- IPDPS 2021
- Readers: Everyone
Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models
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 (modified: 22 Mar 2022)
- Int. J. High Perform. Comput. Appl. 2021
- Readers: Everyone
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications
Shusen Liu, Jim Gaffney, 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
- 2020 (modified: 05 Nov 2022)
- IEEE Trans. Vis. Comput. Graph. 2020
- Readers: Everyone
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets
Sam Ade Jacobs, Jim Gaffney, Tom Benson, Peter B. Robinson, 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 (modified: 06 Nov 2022)
- CLUSTER 2019
- Readers: Everyone
Merlin: Enabling Machine Learning-Ready HPC Ensembles
Jayson 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 et al. (1 additional authors not shown)
- 2019 (modified: 06 Nov 2022)
- CoRR 2019
- Readers: Everyone

View all 26 publications

Co-Authors

View all 81 co-authors