Philip E. Davis

According to our database1, Philip E. Davis authored at least 27 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Streaming Data in HPC Workflows Using ADIOS.
CoRR, 2024

2023
Adaptive elasticity policies for staging-based <i>in situ</i> visualization.
Future Gener. Comput. Syst., May, 2023

LowFive: In Situ Data Transport for High-Performance Workflows.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Benesh: a Framework for Choreographic Coordination of In Situ Workflows.
Proceedings of the 30th IEEE International Conference on High Performance Computing, 2023

Optimizing Data Movement for GPU-Based In-Situ Workflow Using GPUDirect RDMA.
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.
Int. J. High Perform. Comput. Appl., 2022

Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization.
Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

2021
Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges.
CoRR, 2021

An Adaptive Elasticity Policy For Staging Based In-Situ Processing.
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.
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.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

Adaptive Placement of Data Analysis Tasks For Staging Based In-Situ Processing.
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.
Proceedings of the IEEE International Conference on Cluster Computing, 2021

2020
CoREC: Scalable and Resilient In-memory Data Staging for In-situ Workflows.
ACM Trans. Parallel Comput., 2020

ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management.
SoftwareX, 2020

Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows.
CoRR, 2020

Benesh: a Programming Model for Coupled Scientific Workflows.
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.
Proceedings of the IEEE International Conference on Cluster Computing, 2020

2019
Addressing data resiliency for staging based scientific workflows.
Proceedings of the International Conference for High Performance Computing, 2019

Towards a Smart, Internet-Scale Cache Service for Data Intensive Scientific Applications.
Proceedings of the 10th Workshop on Scientific Cloud Computing, 2019

Leveraging Machine Learning for Anticipatory Data Delivery in Extreme Scale In-situ Workflows.
Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

2018
Using Intel Optane Devices for In-situ Data Staging in HPC Workflows.
CoRR, 2018

Stacker: an autonomic data movement engine for extreme-scale data staging-based in-situ workflows.
Proceedings of the International Conference for High Performance Computing, 2018

Scalable Data Resilience for In-memory Data Staging.
Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018


2017
Scalable Parallelization of a Markov Coalescent Genealogy Sampler.
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.
Proceedings of the Euro-Par 2017: Parallel Processing - 23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 28, 2017


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