An Implementation of the Codelet Model. - Joshua Suetterlein; Stéphane Zuckerman; Guang R. Gao (Euro-Par, 2013)

Automatic Locality Exploitation in the Codelet Model. - Chen Chen 067; Yao Wu; Joshua Suetterlein; Long Zheng 001; Minyi Guo; Guang R. Gao (TrustCom/ISPA/IUCC, 2013)

Application characterization at scale: lessons learned from developing a distributed open community runtime system for high performance computing. - Joshua Landwehr; Joshua Suetterlein; Andres Marquez 001; Joseph B. Manzano; Guang R. Gao (Conf. Computing Frontiers, 2016)

Extending the Roofline Model for Asynchronous Many-Task Runtimes. - Joshua D. Suetterlein; Joshua Landwehr; Andrés Márquez 001; Joseph B. Manzano; Guang R. Gao (CLUSTER, 2016)

Asynchronous Runtimes in Action: An Introspective Framework for a Next Gen Runtime. - Joshua Suetterlein; Joshua Landwehr; Andrés Márquez 001; Joseph B. Manzano; Guang R. Gao (IPDPS Workshops, 2016)

Designing Scalable Distributed Memory Models: A Case Study. - Joshua Landwehr; Joshua Suetterlein; Joseph B. Manzano; Andrés Márquez 001; Kevin J. Barker; Guang R. Gao (Conf. Computing Frontiers, 2017)

Verification of the Extended Roofline Model for Asynchronous Many Task Runtimes. - Joshua Suetterlein; Joshua Landwehr; Andres Marquez 001; Joseph B. Manzano; Kevin J. Barker; Guang R. Gao (ESPM2@SC, 2017)

Adaptive Runtime Features for Distributed Graph Algorithms. - Jesun Sahariar Firoz; Marcin Zalewski; Joshua Suetterlein; Andrew Lumsdaine (HiPC, 2018)

TAZeR: Hiding the Cost of Remote I/O in Distributed Scientific Workflows. - Joshua Suetterlein; Ryan D. Friese; Nathan R. Tallent; Malachi Schram (IEEE BigData, 2019)

A Parallel Graph Environment for Real-World Data Analytics Workflows. - Vito Giovanni Castellana; Maurizio Drocco; John Feo; Jesun Sahariar Firoz; Thejaka Amila Kanewala; Andrew Lumsdaine; Joseph B. Manzano; Andres Marquez 001; Marco Minutoli; Joshua Suetterlein; Antonino Tumeo; Marcin Zalewski (DATE, 2019)

Effectively Using Remote I/O For Work Composition in Distributed Workflows. - Ryan D. Friese; Burcu Ozcelik Mutlu; Nathan R. Tallent; Joshua Suetterlein; Jan Strube 001 (IEEE BigData, 2020)

On the Marriage of Asynchronous Many Task Runtimes and Big Data: A Glance. - Joshua Suetterlein; Joseph B. Manzano; Andres Marquez 001; Guang R. Gao (HiPC, 2020)

LC-MEMENTO: A Memory Model for Accelerated Architectures. - Kiran Ranganath; Jesun Firoz; Joshua Suetterlein; Joseph B. Manzano; Andres Marquez 001; Mark Raugas; Daniel Wong 001 (LCPC, 2021)

MAPA: multi-accelerator pattern allocation policy for multi-tenant GPU servers. - Kiran Ranganath; Joshua D. Suetterlein; Joseph B. Manzano; Shuaiwen Leon Song; Daniel Wong 001 (SC, 2021)

Extending an asynchronous runtime system for high throughput applications: A case study. - Joshua Suetterlein; Joseph B. Manzano; Andres Marquez 001; Guang R. Gao (J. Parallel Distributed Comput., 2022)

EXARL-PARS: Parallel Augmented Random Search Using Reinforcement Learning at Scale for Applications in Power Systems. - Himanshu Sharma; Joshua D. Suetterlein; Sumathi Lakshmiranganatha; Thomas Flynn 001; Draguna L. Vrabie; Christine Sweeney; Vinay Ramakrishnaiah (e-Energy (Companion), 2023)

Finding Your Niche: An Evolutionary Approach to HPC Topologies. - Stephen J. Young; Joshua Suetterlein; Jesun Firoz; Joseph B. Manzano; Kevin J. Barker (HPEC, 2023)

HPC Network Simulation Tuning via Automatic Extraction of Hardware Parameters. - Joshua Suetterlein; Stephen J. Young; Jesun Firoz; Joseph B. Manzano; Nathan R. Tallent; Ryan D. Friese; Kevin J. Barker; Timothy Stavenger (HPEC, 2024)

Graph Analytics on Jellyfish topology. - Md Nahid Newaz; Sayan Ghosh; Joshua Suetterlein; Nathan R. Tallent; Md Atiqul Mollah; Ming Hua 003 (IPDPS, 2024)

Automatic Extraction of Network Configurations for Realistic Simulation and Validation. - Joshua Suetterlein; Stephen J. Young; Jesun Firoz; Joseph B. Manzano; Ryan D. Friese; Nathan R. Tallent; Kevin J. Barker; Timothy Stavenger (ISPASS, 2024)

Synchronization for CXL Based Memory. - Joshua Suetterlein; Joseph B. Manzano; Andres Marquez 001 (MEMSYS, 2024)

Assessing the Impact of Distribution Shift on Reinforcement Learning Performance. - Ted Fujimoto; Joshua Suetterlein; Samrat Chatterjee; Auroop R. Ganguly (CoRR, 2024)

Reducing Communication Overhead in Federated Learning for Network Anomaly Detection with Adaptive Client Selection. - William Marfo; Deepak K. Tosh; Shirley V. Moore; Joshua Suetterlein; Joseph B. Manzano (CoRR, 2025)