Supporting High-Performance and High-Throughput Computing for Experimental Science

Author:

Huerta E. A.,Haas Roland,Jha Shantenu,Neubauer Mark,Katz Daniel S.

Funder

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Nuclear and High Energy Physics,Computer Science (miscellaneous),Software

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Spectrally-tuned compact finite-difference schemes with domain decomposition and applications to numerical relativity;Journal of Computational Physics;2024-07

2. Accelerating Scientific Workflows on HPC Platforms with In Situ Processing;2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid);2022-05

3. An Optimal GeoAI Workflow for Pan-Arctic Permafrost Feature Detection from High-Resolution Satellite Imagery;Photogrammetric Engineering & Remote Sensing;2022-03-01

4. Statistically-informed deep learning for gravitational wave parameter estimation;Machine Learning: Science and Technology;2021-11-30

5. GR-Athena++: Puncture Evolutions on Vertex-centered Oct-tree Adaptive Mesh Refinement;The Astrophysical Journal Supplement Series;2021-11-10

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