Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales. - Ian T. Foster; Mark Ainsworth; Bryce Allen; Julie Bessac; Franck Cappello; Jong Youl Choi; Emil M. Constantinescu; Philip E. Davis; Sheng Di; Zichao Wendy Di; Hanqi Guo 001; Scott Klasky; et al. (Euro-Par, 2017)

Scalable Parallelization of a Markov Coalescent Genealogy Sampler. - Philip E. Davis; Adam M. Terwilliger; David Zeitler; Gregory Wolffe (IPDPS Workshops, 2017)

Coupling Exascale Multiphysics Applications: Methods and Lessons Learned. - Jong Youl Choi; Choong-Seock Chang; Julien Dominski; Scott Klasky; Gabriele Merlo; Eric Suchyta; Mark Ainsworth; Bryce Allen; Franck Cappello; Michael Churchill; Philip E. Davis; Sheng Di; et al. (eScience, 2018)

Scalable Data Resilience for In-memory Data Staging. - Shaohua Duan; Pradeep Subedi; Keita Teranishi; Philip E. Davis; Hemanth Kolla; Marc Gamell; Manish Parashar (IPDPS, 2018)

Stacker: an autonomic data movement engine for extreme-scale data staging-based in-situ workflows. - Pradeep Subedi; Philip E. Davis; Shaohua Duan; Scott Klasky; Hemanth Kolla; Manish Parashar (SC, 2018)

Using Intel Optane Devices for In-situ Data Staging in HPC Workflows. - Pradeep Subedi; Philip E. Davis; Juan J. Villalobos; Ivan Rodero; Manish Parashar (CoRR, 2018)

Leveraging Machine Learning for Anticipatory Data Delivery in Extreme Scale In-situ Workflows. - Pradeep Subedi; Philip E. Davis; Manish Parashar (CLUSTER, 2019)

Towards a Smart, Internet-Scale Cache Service for Data Intensive Scientific Applications. - Yubo Qin; Anthony Simonet; Philip E. Davis; Azita Nouri; Zhe Wang 059; Manish Parashar; Ivan Rodero (ScienceCloud@HPDC, 2019)

Addressing data resiliency for staging based scientific workflows. - Shaohua Duan; Pradeep Subedi; Philip E. Davis; Manish Parashar (SC, 2019)

Staging Based Task Execution for Data-driven, In-Situ Scientific Workflows. - Zhe Wang 059; Pradeep Subedi; Matthieu Dorier; Philip E. Davis; Manish Parashar (CLUSTER, 2020)

Benesh: a Programming Model for Coupled Scientific Workflows. - Philip E. Davis; Pradeep Subedi; Shaohua Duan; Lee F. Ricketson; Jeffrey A. F. Hittinger; Manish Parashar (ESPM2@SC, 2020)

Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows. - Zhe Wang 059; Pradeep Subedi; Shaohua Duan; Yubo Qin; Philip E. Davis; Anthony Simonet; Ivan Rodero; Manish Parashar (CoRR, 2020)

ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management. - William F. Godoy; Norbert Podhorszki; Ruonan Wang; Chuck Atkins; Greg Eisenhauer; Junmin Gu; Philip E. Davis; Jong Choi 001; Kai Germaschewski; Kevin A. Huck; Axel Huebl; Mark Kim; et al. (SoftwareX, 2020)

CoREC: Scalable and Resilient In-memory Data Staging for In-situ Workflows. - Shaohua Duan; Pradeep Subedi; Philip E. Davis; Keita Teranishi; Hemanth Kolla; Marc Gamell; Manish Parashar (ACM Trans. Parallel Comput., 2020)

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows. - Pradeep Subedi; Philip E. Davis; Manish Parashar (CLUSTER, 2021)

Adaptive Placement of Data Analysis Tasks For Staging Based In-Situ Processing. - Zhe Wang 059; Pradeep Subedi; Matthieu Dorier; Philip E. Davis; Manish Parashar (HiPC, 2021)

Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows. - Zhe Wang 059; Pradeep Subedi; Matthieu Dorier; Philip E. Davis; Manish Parashar (IPDPS Workshops, 2021)

Transitioning from File-Based HPC Workflows to Streaming Data Pipelines with openPMD and ADIOS2. - Franz Poeschel; Juncheng E; William F. Godoy; Norbert Podhorszki; Scott Klasky; Greg Eisenhauer; Philip E. Davis; Lipeng Wan 001; Ana Gainaru; Junmin Gu; Fabian Koller; René Widera; et al. (SMC, 2021)

An Adaptive Elasticity Policy For Staging Based In-Situ Processing. - Zhe Wang 059; Matthieu Dorier; Pradeep Subedi; Philip E. Davis; Manish Parashar (WORKS, 2021)

Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges. - Azita Nouri; Philip E. Davis; Pradeep Subedi; Manish Parashar (CoRR, 2021)

Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization. - Bo Zhang 120; Pradeep Subedi; Philip E. Davis; Francesco Rizzi; Keita Teranishi; Manish Parashar (CCGRID, 2022)

The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science. - Eric Suchyta; Scott Klasky; Norbert Podhorszki; Matthew Wolf; Abolaji D. Adesoji; Choong-Seock Chang; Jong Choi 001; Philip E. Davis; Julien Dominski; Stéphane Ethier; Ian T. Foster; Kai Germaschewski; et al. (Int. J. High Perform. Comput. Appl., 2022)

Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA. - Bo Zhang 120; Philip E. Davis; Nicolas M. Morales; Zhao Zhang; Keita Teranishi; Manish Parashar (Euro-Par, 2023)

Benesh: a Framework for Choreographic Coordination of In Situ Workflows. - Philip E. Davis; Jacob S. Merson; Pradeep Subedi; Lee F. Ricketson; Cameron W. Smith; Mark S. Shephard; Manish Parashar (HiPC, 2023)

LowFive: In Situ Data Transport for High-Performance Workflows. - Tom Peterka; Dmitriy Morozov; Arnur Nigmetov; Orcun Yildiz; Bogdan Nicolae; Philip E. Davis (IPDPS, 2023)

Adaptive elasticity policies for staging-based in situ visualization. - Zhe Wang 059; Matthieu Dorier; Pradeep Subedi; Philip E. Davis; Manish Parashar (Future Gener. Comput. Syst., 2023)

Dual Channel Dual Staging: Hierarchical and Portable Staging for GPU-Based In-Situ Workflow. - Bo Zhang 120; Philip E. Davis; Zhao Zhang; Keita Teranishi; Manish Parashar (HiPC, 2024)

Streaming Data in HPC Workflows Using ADIOS. - Greg Eisenhauer; Norbert Podhorszki; Ana Gainaru; Scott Klasky; Philip E. Davis; Manish Parashar; Matthew Wolf; Eric Suchtya; Erick Fredj; Vicente Bolea; Franz Pöschel; Klaus Steiniger; et al. (CoRR, 2024)

Fire-D: Analysis and ML-Ready NASA-Centric Remote Sensing of Wildfire and Smoke. - Yuzhou Chen; Nicholas LaHaye; Jae Won Choi; Zhiwei Zhen; Philip E. Davis; Huikyo Lee; Manish Parashar; Yulia R. Gel (Zenodo, 2024)