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2020 – today
- 2024
[i5]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, Michael Bussmann, Richard Pausch, Sunita Chandrasekaran:
Streaming Data in HPC Workflows Using ADIOS. CoRR abs/2410.00178 (2024)- 2023
- [j4]Zhe Wang
, Matthieu Dorier, Pradeep Subedi, Philip E. Davis, Manish Parashar:
Adaptive elasticity policies for staging-based in situ visualization. Future Gener. Comput. Syst. 142: 75-89 (2023) - [c19]Bo Zhang, Philip E. Davis, Nicolas M. Morales, Zhao Zhang, Keita Teranishi, Manish Parashar:
Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA. Euro-Par 2023: 323-338 - [c18]Philip E. Davis, Jacob S. Merson, Pradeep Subedi, Lee F. Ricketson, Cameron W. Smith, Mark S. Shephard, Manish Parashar:
Benesh: a Framework for Choreographic Coordination of In Situ Workflows. HiPC 2023: 298-308 - [c17]Tom Peterka, Dmitriy Morozov, Arnur Nigmetov, Orcun Yildiz, Bogdan Nicolae, Philip E. Davis:
LowFive: In Situ Data Transport for High-Performance Workflows. IPDPS 2023: 985-995 - 2022
- [j3]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:
The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science. Int. J. High Perform. Comput. Appl. 36(1): 106-128 (2022) - [c16]Bo Zhang, Pradeep Subedi, Philip E. Davis, Francesco Rizzi, Keita Teranishi, Manish Parashar:
Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization. CCGRID 2022: 41-50 - 2021
- [c15]Pradeep Subedi, Philip E. Davis, Manish Parashar:
RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows. CLUSTER 2021: 146-156 - [c14]Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar:
Adaptive Placement of Data Analysis Tasks For Staging Based In-Situ Processing. HiPC 2021: 242-251 - [c13]Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar:
Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows. IPDPS Workshops 2021: 960-964 - [c12]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:
Transitioning from File-Based HPC Workflows to Streaming Data Pipelines with openPMD and ADIOS2. SMC 2021: 99-118 - [c11]Zhe Wang, Matthieu Dorier, Pradeep Subedi, Philip E. Davis, Manish Parashar:
An Adaptive Elasticity Policy For Staging Based In-Situ Processing. WORKS 2021: 33-41 - [i4]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:
Transitioning from file-based HPC workflows to streaming data pipelines with openPMD and ADIOS2. CoRR abs/2107.06108 (2021) - [i3]Azita Nouri, Philip E. Davis, Pradeep Subedi, Manish Parashar:
Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges. CoRR abs/2110.13999 (2021) - 2020
- [j2]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:
ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management. SoftwareX 12: 100561 (2020) - [j1]Shaohua Duan, Pradeep Subedi, Philip E. Davis, Keita Teranishi, Hemanth Kolla, Marc Gamell, Manish Parashar:
CoREC: Scalable and Resilient In-memory Data Staging for In-situ Workflows. ACM Trans. Parallel Comput. 7(2): 12:1-12:29 (2020) - [c10]Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar:
Staging Based Task Execution for Data-driven, In-Situ Scientific Workflows. CLUSTER 2020: 209-220 - [c9]Philip E. Davis, Pradeep Subedi, Shaohua Duan, Lee F. Ricketson, Jeffrey A. F. Hittinger, Manish Parashar:
Benesh: a Programming Model for Coupled Scientific Workflows. ESPM2@SC 2020: 1-9 - [i2]Zhe Wang, Pradeep Subedi, Shaohua Duan, Yubo Qin, Philip E. Davis, Anthony Simonet, Ivan Rodero, Manish Parashar:
Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows. CoRR abs/2004.10381 (2020)
2010 – 2019
- 2019
- [c8]Pradeep Subedi, Philip E. Davis, Manish Parashar:
Leveraging Machine Learning for Anticipatory Data Delivery in Extreme Scale In-situ Workflows. CLUSTER 2019: 1-11 - [c7]Yubo Qin, Anthony Simonet, Philip E. Davis, Azita Nouri, Zhe Wang, Manish Parashar, Ivan Rodero:
Towards a Smart, Internet-Scale Cache Service for Data Intensive Scientific Applications. ScienceCloud@HPDC 2019: 11-18 - [c6]Shaohua Duan, Pradeep Subedi, Philip E. Davis, Manish Parashar:
Addressing data resiliency for staging based scientific workflows. SC 2019: 87:1-87:22 - 2018
- [c5]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:
Coupling Exascale Multiphysics Applications: Methods and Lessons Learned. eScience 2018: 442-452 - [c4]Shaohua Duan, Pradeep Subedi, Keita Teranishi, Philip E. Davis, Hemanth Kolla, Marc Gamell, Manish Parashar:
Scalable Data Resilience for In-memory Data Staging. IPDPS 2018: 105-115 - [c3]Pradeep Subedi, Philip E. Davis, Shaohua Duan, Scott Klasky, Hemanth Kolla, Manish Parashar:
Stacker: an autonomic data movement engine for extreme-scale data staging-based in-situ workflows. SC 2018: 73:1-73:11 - [i1]Pradeep Subedi, Philip E. Davis, Juan J. Villalobos, Ivan Rodero, Manish Parashar:
Using Intel Optane Devices for In-situ Data Staging in HPC Workflows. CoRR abs/1807.09651 (2018) - 2017
- [c2]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:
Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales. Euro-Par 2017: 3-19 - [c1]Philip E. Davis, Adam M. Terwilliger, David Zeitler, Gregory Wolffe:
Scalable Parallelization of a Markov Coalescent Genealogy Sampler. IPDPS Workshops 2017: 293-302
Coauthor Index
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