Mapping the Single-Row Routing Problem to a Hypercube. - Shaharuddin Salleh; Albert Y. Zomaya; David Hysom (PDPTA, 1997)

Parallel Computation of ILU(k) Preconditioners Without Serial Bottlenecks. - David Hysom; Alex Pothen (PP, 1999)

Efficient Parallel Computation of ILU(k) Preconditioners. - David Hysom; Alex Pothen (SC, 1999)

A Scalable Parallel Algorithm for Incomplete Factor Preconditioning. - David Hysom; Alex Pothen (SIAM J. Sci. Comput., 2001)

New Sequential and Scalable Parallel Algorithms for Incomplete Factor Preconditioning. - David Hysom (2001)

Enhancing scalability of parallel structured AMR calculations. - Andrew M. Wissink; David Hysom; Richard D. Hornung (ICS, 2003)

Multi-Criterion Active Learning in Conditional Random Fields. - Christopher T. Symons; Nagiza F. Samatova; Ramya Krishnamurthy; Byung-Hoon Park; Tarik Umar; David Buttler; Terence Critchlow; David Hysom (ICTAI, 2006)

Parallel clustering algorithms for structured AMR. - Brian T. N. Gunney; Andrew M. Wissink; David Hysom (J. Parallel Distributed Comput., 2006)

Coreference Resolution with Reconcile. - Veselin Stoyanov; Claire Cardie; Nathan Gilbert; Ellen Riloff; David Buttler; David Hysom (ACL (2), 2010)

Scalable metagenomic taxonomy classification using a reference genome database. - Sasha Ames; David A. Hysom; Shea N. Gardner; G. Scott Lloyd; Maya B. Gokhale; Jonathan E. Allen (Bioinform., 2013)

Design and Optimization of a Metagenomics Analysis Workflow for NVRAM. - Sasha Ames; Jonathan E. Allen; David A. Hysom; G. Scott Lloyd; Maya B. Gokhale (IPDPS Workshops, 2014)

Multiplex Degenerate Primer Design for Targeted Whole Genome Amplification of Many Viral Genomes. - Shea N. Gardner; Crystal J. Jaing; Maher M. Elsheikh; José Peña; David A. Hysom; Monica K. Borucki (Adv. Bioinformatics, 2014)

Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. - 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; et al. (CLUSTER, 2019)

Merlin: Enabling Machine Learning-Ready HPC Ensembles. - 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; et al. (CoRR, 2019)

Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. - Shusen Liu 001; 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; et al. (IEEE Trans. Vis. Comput. Graph., 2020)

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 (Int. J. High Perform. Comput. Appl., 2021)