Towards Scaling Parallel Seismic Raytracing

Allen D. Malony; Mohammad Alaul Haque Monil; Craig Rasmusen; Kevin Huck; Joseph Byrnes; Doug Toomey

doi:10.1109/CSE-EUC-DCABES.2016.189

Towards Scaling Parallel Seismic Raytracing

Allen D. Malony, Mohammad Alaul Haque Monil, Craig Rasmusen, Kevin Huck, Joseph Byrnes, Doug Toomey

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Marine geologists use seismic tomography techniques to determine the 3D geophysical structure of the ocean floor. At the heart of seismic tomography methods is a forward solver used to compute minimum travel times from all locations in a earth model to sensors used in seismic experiments. The Stingray seismic raytracer was originally based on an adaption of Dijkstra's single-source shortest-path algorithm. Unfortunately, the algorithm's inherent sequential nature limits its scalability. Our new parallel Stingray implementations are based on an iterative data parallel algorithm and demonstrates scalable performance in both time and problem size. Results are presented for OpenMP and MPI experiments on seismic models of significantly larger size than Stingray has processed before.

Original language	English
Title of host publication	Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	225-233
Number of pages	9
ISBN (Electronic)	9781509035939
DOIs	https://doi.org/10.1109/CSE-EUC-DCABES.2016.189
State	Published - Jul 14 2017
Externally published	Yes
Event	19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016 - Paris, France Duration: Aug 24 2016 → Aug 26 2016

Publication series

Name	Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016

Conference

Conference	19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016
Country/Territory	France
City	Paris
Period	08/24/16 → 08/26/16

Keywords

data parallel
marine seismology
raytracing
shortest path
tomography

Access to Document

10.1109/CSE-EUC-DCABES.2016.189

Cite this

Malony, A. D., Monil, M. A. H., Rasmusen, C., Huck, K., Byrnes, J., & Toomey, D. (2017). Towards Scaling Parallel Seismic Raytracing. In Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016 (pp. 225-233). Article 7982251 (Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSE-EUC-DCABES.2016.189

Malony, Allen D. ; Monil, Mohammad Alaul Haque ; Rasmusen, Craig et al. / Towards Scaling Parallel Seismic Raytracing. Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 225-233 (Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016).

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abstract = "Marine geologists use seismic tomography techniques to determine the 3D geophysical structure of the ocean floor. At the heart of seismic tomography methods is a forward solver used to compute minimum travel times from all locations in a earth model to sensors used in seismic experiments. The Stingray seismic raytracer was originally based on an adaption of Dijkstra's single-source shortest-path algorithm. Unfortunately, the algorithm's inherent sequential nature limits its scalability. Our new parallel Stingray implementations are based on an iterative data parallel algorithm and demonstrates scalable performance in both time and problem size. Results are presented for OpenMP and MPI experiments on seismic models of significantly larger size than Stingray has processed before.",

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Malony, AD, Monil, MAH, Rasmusen, C, Huck, K, Byrnes, J & Toomey, D 2017, Towards Scaling Parallel Seismic Raytracing. in Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016., 7982251, Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016, Institute of Electrical and Electronics Engineers Inc., pp. 225-233, 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016, Paris, France, 08/24/16. https://doi.org/10.1109/CSE-EUC-DCABES.2016.189

Towards Scaling Parallel Seismic Raytracing. / Malony, Allen D.; Monil, Mohammad Alaul Haque; Rasmusen, Craig et al.
Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 225-233 7982251 (Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Byrnes, Joseph

AU - Toomey, Doug

PY - 2017/7/14

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AB - Marine geologists use seismic tomography techniques to determine the 3D geophysical structure of the ocean floor. At the heart of seismic tomography methods is a forward solver used to compute minimum travel times from all locations in a earth model to sensors used in seismic experiments. The Stingray seismic raytracer was originally based on an adaption of Dijkstra's single-source shortest-path algorithm. Unfortunately, the algorithm's inherent sequential nature limits its scalability. Our new parallel Stingray implementations are based on an iterative data parallel algorithm and demonstrates scalable performance in both time and problem size. Results are presented for OpenMP and MPI experiments on seismic models of significantly larger size than Stingray has processed before.

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M3 - Conference contribution

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Malony AD, Monil MAH, Rasmusen C, Huck K, Byrnes J, Toomey D. Towards Scaling Parallel Seismic Raytracing. In Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 225-233. 7982251. (Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016). doi: 10.1109/CSE-EUC-DCABES.2016.189

Towards Scaling Parallel Seismic Raytracing

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Keywords

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