Partitioning and Dynamic Load Balancing of Adaptive Hybrid Grids for Large-Scale Turbulent Flow Simulations. - Tommy Minyard; Yannis Kallinderis; Karl W. Schulz (HICSS (1), 1996)

Scientific formats for object-relational database systems: a study of suitability and performance. - Shirley Cohen; Patrick Hurley; Karl W. Schulz; William L. Barth; Brad Benton (SIGMOD Rec., 2006)

Message from the conference chairs, Cluster 2007. - Karl W. Schulz; Kent F. Milfeld (CLUSTER, 2007)

Quantifying performance benefits of overlap using MPI-2 in a seismic modeling application. - Sreeram Potluri; Ping Lai; Karen A. Tomko; Sayantan Sur; Yifeng Cui; Mahidhar Tatineni; Karl W. Schulz; William L. Barth; Amitava Majumdar 001; Dhabaleswar K. Panda 001 (ICS, 2010)

Petascale I/O using HDF-5. - Nicholas Malaya; Karl W. Schulz; Robert D. Moser (TG, 2010)

Design and Evaluation of Network Topology-/Speed- Aware Broadcast Algorithms for InfiniBand Clusters. - Hari Subramoni; Krishna Chaitanya Kandalla; Jérôme Vienne; Sayantan Sur; Bill Barth; Karen A. Tomko; Robert T. McLay; Karl W. Schulz; Dhabaleswar K. Panda 001 (CLUSTER, 2011)

The Parallel C++ Statistical Library 'QUESO': Quantification of Uncertainty for Estimation, Simulation and Optimization. - Ernesto E. Prudencio; Karl W. Schulz (Euro-Par Workshops (1), 2011)

Best practices for the deployment and management of production HPC clusters. - Robert T. McLay; Karl W. Schulz; William L. Barth; Tommy Minyard (SC State of the Practice Reports, 2011)

Design of a scalable InfiniBand topology service to enable network-topology-aware placement of processes. - Hari Subramoni; Sreeram Potluri; Krishna Chaitanya Kandalla; Bill Barth; Jérôme Vienne; Jeff Keasler; Karen A. Tomko; Karl W. Schulz; Adam Moody; Dhabaleswar K. Panda 001 (SC, 2012)

A distributed memory out-of-core method on HPC clusters and its application to quantum chemistry applications. - Christopher S. Simmons; Karl W. Schulz (XSEDE, 2012)

Visual Analytics for Finding Critical Structures in Massive Time-Varying Turbulent-Flow Simulations. - Kelly P. Gaither; Hank Childs; Karl W. Schulz; Cyrus Harrison; William L. Barth; Diego Donzis; Pui-Kuen Yeung (IEEE Computer Graphics and Applications, 2012)

Design of network topology aware scheduling services for large InfiniBand clusters. - Hari Subramoni; Devendar Bureddy; Krishna Chaitanya Kandalla; Karl W. Schulz; Bill Barth; Jonathan L. Perkins; Mark Daniel Arnold; Dhabaleswar K. Panda 001 (CLUSTER, 2013)

Algorithms for high-throughput disk-to-disk sorting. - Hari Sundar; Dhairya Malhotra; Karl W. Schulz (SC, 2013)

MASA : a library for verification using manufactured and analytical solutions. - Nicholas Malaya; Kemelli C. Estacio-Hiroms; Roy H. Stogner; Karl W. Schulz; Paul T. Bauman; Graham F. Carey (Eng. Comput., 2013)

Designing Topology-Aware Communication Schedules for Alltoall Operations in Large InfiniBand Clusters. - Hari Subramoni; Krishna Chaitanya Kandalla; Jithin Jose; Karen Tomko; Karl W. Schulz; Dmitry Pekurovsky; Dhabaleswar K. Panda 001 (ICPP, 2014)

Designing Scalable Out-of-core Sorting with Hybrid MPI+PGAS Programming Models. - Jithin Jose; Sreeram Potluri; Hari Subramoni; Xiaoyi Lu; Khaled Hamidouche; Karl W. Schulz; Hari Sundar; Dhabaleswar K. Panda 001 (PGAS, 2014)

Customizing OpenHPC: integrating additional software and provisioning new services including open ondemand. - Christopher S. Simmons; Karl W. Schulz; Derek Simmel (PEARC Companion, 2020)

Evaluation of Clustering Techniques for GPS Phenotyping Using Mobile Sensor Data. - Zachary S. Tschirhart; Karl W. Schulz (PEARC, 2020)

Collecting and analyzing smartphone sensor data for health. - Justin A. Drake; Karl W. Schulz; Radek Bukowski; Kelly P. Gaither (PEARC, 2021)

Parla: A Python Orchestration System for Heterogeneous Architectures. - Hochan Lee; William Ruys; Ian Henriksen; Arthur Peters; Yineng Yan; Sean Stephens; Bozhi You; Henrique Fingler; Martin Burtscher; Milos Gligoric 001; Karl W. Schulz; Keshav Pingali; et al. (SC, 2022)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

Scalable Training of Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN. - Massimiliano Lupo Pasini; Jong Youl Choi; Kshitij Mehta; Pei Zhang; David M. Rogers 001; Jonghyun Bae; Khaled Z. Ibrahim; Ashwin M. Aji; Karl W. Schulz; Jorda Polo; Prasanna Balaprakash (CoRR, 2024)

Scalable training of trustworthy and energy-efficient predictive graph foundation models for atomistic materials modeling: a case study with HydraGNN. - Massimiliano Lupo Pasini; Jong Youl Choi; Kshitij Mehta; Pei Zhang; David M. Rogers 001; Jonghyun Bae; Khaled Z. Ibrahim; Ashwin M. Aji; Karl W. Schulz; Jordà Polo; Prasanna Balaprakash (J. Supercomput., 2025)

Multi-task parallelism for robust pre-training of graph foundation models on multi-source, multi-fidelity atomistic modeling data. - Massimiliano Lupo Pasini; Jong Youl Choi; Pei Zhang; Kshitij Mehta; Rylie Weaver; Ashwin M. Aji; Karl W. Schulz; Jorda Polo; Prasanna Balaprakash (CoRR, 2025)