Philip E. Davis

According to our database, Philip E. Davis authored at least 26 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Adaptive elasticity policies for staging-based <i>in situ</i> visualization.

Zhe Wang, Matthieu Dorier, Pradeep Subedi, Philip E. Davis, Manish Parashar

Future Gener. Comput. Syst., May, 2023

LowFive: In Situ Data Transport for High-Performance Workflows.

Tom Peterka, Dmitriy Morozov, Arnur Nigmetov, Orcun Yildiz, Bogdan Nicolae, Philip E. Davis

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Benesh: a Framework for Choreographic Coordination of In Situ Workflows.

Philip E. Davis, Jacob Merson, Pradeep Subedi, Lee F. Ricketson, Cameron W. Smith, Mark S. Shephard, Manish Parashar

Proceedings of the 30th IEEE International Conference on High Performance Computing, 2023

Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA.

Bo Zhang, Philip E. Davis, Nicolas Morales, Zhao Zhang, Keita Teranishi, Manish Parashar

Proceedings of the Euro-Par 2023: Parallel Processing - 29th International Conference on Parallel and Distributed Computing, Limassol, Cyprus, August 28, 2023

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, Philip E. Davis, Julien Dominski, Stéphane Ethier, Ian T. Foster, Kai Germaschewski, Berk Geveci, Chris Harris, Kevin A. Huck, Qing Liu, Jeremy Logan, Kshitij Mehta, Gabriele Merlo, Shirley V. Moore, Todd S. Munson, Manish Parashar, David Pugmire, Mark S. Shephard, Cameron W. Smith, Pradeep Subedi, Lipeng Wan, Ruonan Wang, Shuangxi Zhang

Int. J. High Perform. Comput. Appl., 2022

Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization.

Bo Zhang, Pradeep Subedi, Philip E. Davis, Francesco Rizzi, Keita Teranishi, Manish Parashar

Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

2021

Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges.

Azita Nouri, Philip E. Davis, Pradeep Subedi, Manish Parashar

CoRR, 2021

An Adaptive Elasticity Policy For Staging Based In-Situ Processing.

Zhe Wang, Matthieu Dorier, Pradeep Subedi, Philip E. Davis, Manish Parashar

Proceedings of the 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 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, Ana Gainaru, Junmin Gu, Fabian Koller, René Widera, Michael Bussmann, Axel Huebl

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows.

Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar

Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

Adaptive Placement of Data Analysis Tasks For Staging Based In-Situ Processing.

Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar

Proceedings of the 28th IEEE International Conference on High Performance Computing, 2021

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows.

Pradeep Subedi, Philip E. Davis, Manish Parashar

Proceedings of the IEEE International Conference on Cluster Computing, 2021

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

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, Kai Germaschewski, Kevin A. Huck, Axel Huebl, Mark Kim, James Kress, Tahsin M. Kurç, Qing Liu, Jeremy Logan, Kshitij Mehta, George Ostrouchov, Manish Parashar, Franz Poeschel, David Pugmire, Eric Suchyta, Keichi Takahashi, Nick Thompson, Seiji Tsutsumi, Lipeng Wan, Matthew Wolf, Kesheng Wu, Scott Klasky

SoftwareX, 2020

Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows.

Zhe Wang, Pradeep Subedi, Shaohua Duan, Yubo Qin, Philip E. Davis, Anthony Simonet, Ivan Rodero, Manish Parashar

CoRR, 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

Proceedings of the 5th IEEE/ACM International Workshop on Extreme Scale Programming Models and Middleware, 2020

Staging Based Task Execution for Data-driven, In-Situ Scientific Workflows.

Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar

Proceedings of the IEEE International Conference on Cluster Computing, 2020

2019

Addressing data resiliency for staging based scientific workflows.

Shaohua Duan, Pradeep Subedi, Philip E. Davis, Manish Parashar

Proceedings of the International Conference for High Performance Computing, 2019

Towards a Smart, Internet-Scale Cache Service for Data Intensive Scientific Applications.

Yubo Qin, Anthony Simonet, Philip E. Davis, Azita Nouri, Zhe Wang, Manish Parashar, Ivan Rodero

Proceedings of the 10th Workshop on Scientific Cloud Computing, 2019

Leveraging Machine Learning for Anticipatory Data Delivery in Extreme Scale In-situ Workflows.

Pradeep Subedi, Philip E. Davis, Manish Parashar

Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

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

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

Proceedings of the International Conference for High Performance Computing, 2018

Scalable Data Resilience for In-memory Data Staging.

Shaohua Duan, Pradeep Subedi, Keita Teranishi, Philip E. Davis, Hemanth Kolla, Marc Gamell, Manish Parashar

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

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, Greg Eisenhauer, Stéphane Ethier, Ian T. Foster, Berk Geveci, Hanqi Guo, Kevin A. Huck, Frank Jenko, Mark Kim, James Kress, Seung-Hoe Ku, Qing Liu, Jeremy Logan, Allen D. Malony, Kshitij Mehta, Kenneth Moreland, Todd S. Munson, Manish Parashar, Tom Peterka, Norbert Podhorszki, Dave Pugmire, Ozan Tugluk, Ruonan Wang, Ben Whitney, Matthew Wolf, Chad Wood

Proceedings of the 14th IEEE International Conference on e-Science, 2018

2017

Scalable Parallelization of a Markov Coalescent Genealogy Sampler.

Philip E. Davis, Adam M. Terwilliger, David Zeitler, Gregory Wolffe

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium Workshops, 2017

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, Scott Klasky, Kerstin Kleese van Dam, Tahsin M. Kurç, Qing Liu, Abid Malik, Kshitij Mehta, Klaus Mueller, Todd S. Munson, George Ostrouchov, Manish Parashar, Tom Peterka, Line Pouchard, Dingwen Tao, Ozan Tugluk, Stefan M. Wild, Matthew Wolf, Justin M. Wozniak, Wei Xu, Shinjae Yoo

Proceedings of the Euro-Par 2017: Parallel Processing - 23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 28, 2017