Travis Johnston

15 papers C 2Misc 1Journal 7Unranked 5
YearRankTypeTitle / Venue / Authors
2022 J jnl
Building High-Throughput Neural Architecture Search Workflows via a Decoupled Fitness Prediction Engine.
IEEE Trans. Parallel Distributed Syst.
Ariel Keller Rorabaugh, Silvina Caíno-Lores, Travis Johnston, Michela Taufer
2021 J jnl
Co-design Center for Exascale Machine Learning Technologies (ExaLearn).
Int. J. High Perform. Comput. Appl.
Francis J. Alexander, James Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon
2021 J jnl
PEng4NN: An Accurate Performance Estimation Engine for Efficient Automated Neural Network Architecture Search.
CoRR
Ariel Keller Rorabaugh, Silvina Caíno-Lores, Michael R. Wyatt II, Travis Johnston, Michela Taufer
2020 J jnl
Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks.
CoRR
Mihaela Dimovska, Travis Johnston, Catherine D. Schuman, J. Parker Mitchell, Thomas E. Potok
2020 — conf
Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach.
IEEE BigData
Cristina Garcia-Cardona, Ramakrishnan Kannan, Travis Johnston, Thomas Proffen, Sudip K. Seal
2019 — conf
A Novel Pruning Method for Convolutional Neural Networks Based off Identifying Critical Filters.
PEARC
Mihaela Dimovska, Travis Johnston
2019 J jnl
Creating a portable, high-level graph analytics paradigm for compute and data-intensive applications.
Int. J. High Perform. Comput. Netw.
Robert Searles, Stephen Herbein, Travis Johnston, Michela Taufer, Sunita Chandrasekaran
2019 — conf
Learning to Predict Material Structure from Neutron Scattering Data.
IEEE BigData
Cristina Garcia-Cardona, Ramakrishnan Kannan, Travis Johnston, Thomas Proffen, Katharine Page, Sudip K. Seal
2019 — conf
Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks.
UEMCON
Mihaela Dimovska, Travis Johnston, Catherine D. Schuman, J. Parker Mitchell, Thomas E. Potok
2017 J jnl
Cospectral mates for the union of some classes in the Johnson association scheme.
CoRR
Sebastian M. Cioaba, Travis Johnston, Matt McGinnis
2016 — conf
Development of a Scalable Method for Creating Food Groups Using the NHANES Dataset and MapReduce.
BCB
Michael R. Wyatt II, Travis Johnston, Mia Papas, Michela Taufer
2016 C conf
HYPPO: A Hybrid, Piecewise Polynomial Modeling Technique for Non-Smooth Surfaces.
SBAC-PAD
Travis Johnston, Connor Zanin, Michela Taufer
2015 J jnl
It-Situ Data Analysis of Protein Folding Trajectories.
CoRR
Travis Johnston, Boyu Zhang, Adam Liwo, Silvia Crivelli, Michela Taufer
2015 C conf
On the Need for Reproducible Numerical Accuracy through Intelligent Runtime Selection of Reduction Algorithms at the Extreme Scale.
CLUSTER
Dylan Chapp, Travis Johnston, Michela Taufer
2015 Misc conf
Performance Tuning of MapReduce Jobs Using Surrogate-based Modeling.
ICCS
Travis Johnston, Mohammad Alsulmi, Pietro Cicotti, Michela Taufer