Implementing the Palomar Transient Factory Real-Time Detection Pipeline in GLADE: Results and Observations. - Florin Rusu; Peter Nugent; Kesheng Wu (DNIS, 2014)

PATHA: Performance Analysis Tool for HPC Applications. - Wucherl Yoo; Michelle Koo; Yi Cao; Alex Sim; Peter Nugent; Kesheng Wu (IPCCC, 2015)

The Palomar transient factory. - Peter Nugent; Yi Cao; Mansi M. Kasliwal (Visualization and Data Analysis, 2015)

High Energy Physics Forum for Computational Excellence: Working Group Reports (I. Applications Software II. Software Libraries and Tools III. Systems). - Salman Habib 002; Robert Roser; Tom LeCompte; Zach Marshall; Anders Borgland; Brett Viren; Peter Nugent; Makoto Asai; Lothar Bauerdick; Hal Finkel; Steven Gottlieb; Stefan Hoeche; et al. (CoRR, 2015)

Pattern avoidance in forests of binary shrubs. - David I. Bevan; Derek Levin; Peter Nugent; Jay Pantone; Lara Pudwell; Manda Riehl; M. L. Tlachac (Discret. Math. Theor. Comput. Sci., 2016)

Parallel Variable Selection for Effective Performance Prediction. - Jonathan Wang; Wucherl Yoo; Alex Sim; Peter Nugent; Kesheng Wu (CCGrid, 2017)

Incremental View Maintenance over Array Data. - Weijie Zhao 001; Florin Rusu; Bin Dong 002; Kesheng Wu; Peter Nugent (SIGMOD Conference, 2017)

Distributed caching for processing raw arrays. - Weijie Zhao 001; Florin Rusu; Bin Dong 002; Kesheng Wu; Anna Y. Q. Ho; Peter Nugent (SSDBM, 2018)

Distributed Caching for Complex Querying of Raw Arrays. - Weijie Zhao 001; Florin Rusu; Bin Dong 002; Kesheng Wu; Anna Y. Q. Ho; Peter Nugent (CoRR, 2018)

Automatic identification and classification of Palomar Transient Factory astrophysical objects in GLADE. - Weijie Zhao 001; Florin Rusu; Kesheng Wu; Peter Nugent (Int. J. Comput. Sci. Eng., 2018)

Predicting Resource Requirement in Intermediate Palomar Transient Factory Workflow. - Qiao Kang; Alex Sim; Peter Nugent; Sunwoo Lee 001; Wei-keng Liao; Ankit Agrawal 001; Alok N. Choudhary; Kesheng Wu (CCGRID, 2020)

Asynchronous I/O Strategy for Large-Scale Deep Learning Applications. - Sunwoo Lee 001; Qiao Kang; Kewei Wang 002; Jan Balewski; Alex Sim; Ankit Agrawal 001; Alok N. Choudhary; Peter Nugent; Kesheng Wu; Wei-keng Liao (HiPC, 2021)

Co-design Center for Exascale Machine Learning Technologies (ExaLearn). - Francis J. Alexander; James A. Ang; Jenna A. Bilbrey; Jan Balewski; Tiernan Casey; Ryan Chard; Jong Choi 001; Sutanay Choudhury; Bert J. Debusschere; Anthony M. DeGennaro; Nikoli Dryden; J. Austin Ellis; et al. (Int. J. High Perform. Comput. Appl., 2021)

The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism. - Yosuke Oyama; Naoya Maruyama; Nikoli Dryden; Erin McCarthy; Peter Harrington; Jan Balewski; Satoshi Matsuoka; Peter Nugent; Brian Van Essen (IEEE Trans. Parallel Distributed Syst., 2021)

Using Multi-Resolution Data to Accelerate Neural Network Training in Scientific Applications. - Kewei Wang 002; Sunwoo Lee 001; Jan Balewski; Alex Sim; Peter Nugent; Ankit Agrawal 001; Alok N. Choudhary; Kesheng Wu; Wei-Keng Liao (CCGRID, 2022)

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery. - Yulun Wu; Nicholas Choma; Andrew Deru Chen; Mikaela Cashman; Érica Teixeira Prates; Verónica G. Melesse Vergara; Manesh Shah; Austin Clyde; Thomas S. Brettin; Wibe Albert de Jong; Neeraj Kumar; Martha S. Head; et al. (ICLR, 2022)

Cross-Facility Workflows: Case Studies with Active Experiments. - Nicholas Tyler; Robert A. Knop Jr.; Deborah Bard; Peter Nugent (WORKS@SC, 2022)

FAIR Universe HiggsML Uncertainty Challenge Competition. - Wahid Bhimji; Paolo Calafiura; Ragansu Chakkappai; Yuan-Tang Chou; Sascha Diefenbacher; Jordan Dudley; Steven Farrell; Aishik Ghosh; Isabelle Guyon; Chris Harris; Shih-Chieh Hsu; Elham E Khoda; et al. (CoRR, 2024)