Elise Jennings

11 papers Journal 7Unranked 4
YearRankTypeTitle / Venue / Authors
2024 — conf
$$ : A Quantum Emulation Workbench for Benchmark Construction and Application Development.
Euro-Par Workshops (1)
Elise Jennings, Martin Rüfenacht, Stefan Kister
2024 — conf
A Framework and Methodology for Performance Prediction of HPC Workloads.
PPAM (3)
Júlia Orteu, Marc Clascà, Jesús Labarta, Elise Jennings, Stefan Andersson, Marta Garcia-Gasulla
2022 J jnl
A Kubernetes 'Bridge' operator between cloud and external resources.
CoRR
Boris Lublinsky, Elise Jennings, Viktória Spisaková
2021 J jnl
Bayesian neural networks at scale: a performance analysis and pruning study.
J. Supercomput.
Himanshu Sharma, Elise Jennings
2020 J jnl
Bayesian Neural Networks at Scale: A Performance Analysis and Pruning Study.
CoRR
Himanshu Sharma, Elise Jennings
2020 J jnl
Deploying deep learning in OpenFOAM with TensorFlow.
CoRR
Romit Maulik, Himanshu Sharma, Saumil Patel, Bethany Lusch, Elise Jennings
2019 — conf
A Generalized Statistics-Based Model for Predicting Network-Induced Variability.
PMBS@SC
Sudheer Chunduri, Elise Jennings, Kevin Harms, Christopher Knight, Scott Parker
2019 J jnl
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era.
CoRR
Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew J. Graham, William Gropp, Anushri Gupta, Roland Haas, Eliu A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr V. Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, Mark S. Neubauer, Steve Oberlin, Alexander Reinefeld, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alexander G. Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta Miksztai-Réthey, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao
2019 J jnl
Enabling real-time multi-messenger astrophysics discoveries with deep learning.
CoRR
Eliu A. Huerta, Gabrielle Allen, Igor Andreoni, Javier Mauricio Antelis, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew J. Graham, William Gropp, Robert A. Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr V. Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Márka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark S. Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alexander G. Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipocz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao
2019 — conf
Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping.
DLS@SC
Wushi Dong, Nicola J. Ferrier, Narayanan Kasthuri, Peter Littlewood, Murat Keçeli, Rafael Vescovi, Hanyu Li, Corey Adams, Elise Jennings, Samuel Flender, Thomas D. Uram, Venkatram Vishwanath
2015 J jnl
CosmoSIS: Modular cosmological parameter estimation.
Astron. Comput.
Joe Zuntz, Marc F. Paterno, Elise Jennings, Douglas H. Rudd, Alessandro Manzotti, Scott Dodelson, Sarah Bridle, Saba Sehrish, Jim Kowalkowski