poster

GPU Optimizations for Atmospheric Chemical Kinetics

Authors:

Theodoros Christoudias,

Timo Kirfel,

Astrid Kerkweg,

Domenico Taraborrelli,

Georges-Emmanuel Moulard,

Erwan Raffin,

Victor Azizi,

Gijs van den Oord,

Ben van WerkhovenAuthors Info & Claims

HPCAsia '21: The International Conference on High Performance Computing in Asia-Pacific Region

Pages 136 - 138

https://doi.org/10.1145/3432261.3439863

Published: 20 January 2021 Publication History

Get Access

Abstract

We present a series of optimizations to alleviate stack memory overflow issues and improve overall performance of GPU computational kernels in atmospheric chemical kinetics model simulations. We use heap memory in numerical solvers for stiff ODEs, move chemical reaction constants and tracer concentration arrays from stack to global memory, use direct pointer indexing for array memory access, and use CUDA streams to overlap computation with memory transfer to the device. Overall, an order of magnitude reduction in GPU memory requirements is achieved, allowing for simultaneous offloading from multiple MPI processes per node and/or increasing the chemical mechanism complexity.

References

[1]

Michail Alvanos and Theodoros Christoudias. 2017. GPU-accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model (version 2.52). Geoscientific Model Development 10, 10 (2017), 3679.

Crossref

Google Scholar

[2]

Michail Alvanos and Theodoros Christoudias. 2019. Accelerating Atmospheric Chemical Kinetics for Climate Simulations. IEEE Transactions on Parallel and Distributed Systems 30, 11 (2019), 2396–2407.

Digital Library

Google Scholar

[3]

Theodoros Christoudias and Michail Alvanos. 2016. Accelerated chemical kinetics in the EMAC chemistry-climate model. In 2016 International Conference on High Performance Computing & Simulation (HPCS). IEEE, 886–889.

Crossref

Google Scholar

[4]

Patrick Jöckel, Astrid Kerkweg, Andrea Pozzer, Rolf Sander, Holger Tost, Hella Riede, Andreas Baumgaertner, Sergey Gromov, and Bastian Kern. 2010. Development cycle 2 of the modular earth submodel system (MESSy2). Geoscientific Model Development 3 (2010), 717–752.

Crossref

Google Scholar

[5]

Jülich Supercomputing Centre. 2018. JURECA: Modular supercomputer at Jülich Supercomputing Centre. Journal of large-scale research facilities 4, A132 (2018). https://doi.org/10.17815/jlsrf-4-121-1

Crossref

Google Scholar

[6]

E Roeckner, R Brokopf, M Esch, MA Giorgetta, S Hagemann, L Kornblueh, E Manzini, U Schlese, and U Schulzweida. 2006. Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model. Journal of Climate 19, 16 (2006), 3771–3791.

Crossref

Google Scholar

[7]

R. Sander, A. Baumgaertner, D. Cabrera-Perez, F. Frank, S. Gromov, J.-U. Grooß, H. Harder, V. Huijnen, P. Jöckel, V. A. Karydis, K. E. Niemeyer, A. Pozzer, H. Riede, M. G. Schultz, D. Taraborrelli, and S. Tauer. 2019. The community atmospheric chemistry box model CAABA/MECCA-4.0. Geoscientific Model Development 12, 4 (2019), 1365–1385. https://doi.org/10.5194/gmd-12-1365-2019

Crossref

Google Scholar

[8]

Ben van Werkhoven, Jason Maassen, Frank J Seinstra, and Henri E Bal. 2014. Performance models for CPU-GPU data transfers. In 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. IEEE, 11–20.

Digital Library

Google Scholar

Cited By

View all

Bishnoi AStein OMeyer CRedler REicker NHaak HHoffmann LKlocke DKornblueh LSuarez E(2024)Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rcGeoscientific Model Development10.5194/gmd-17-261-202417:1(261-273)Online publication date: 12-Jan-2024
https://doi.org/10.5194/gmd-17-261-2024
Sophocleous KChristoudias T(2022)Reduced-Precision Chemical Kinetics in Atmospheric ModelsAtmosphere10.3390/atmos1309141813:9(1418)Online publication date: 2-Sep-2022
https://doi.org/10.3390/atmos13091418

Index Terms

GPU Optimizations for Atmospheric Chemical Kinetics

Index terms have been assigned to the content through auto-classification.

Recommendations

Architecture-Aware Mapping and Optimization on a 1600-Core GPU
ICPADS '11: Proceedings of the 2011 IEEE 17th International Conference on Parallel and Distributed Systems

The graphics processing unit (GPU) continues to make in-roads as a computational accelerator for high-performance computing (HPC). However, despite its increasing popularity, mapping and optimizing GPU code remains a difficult task, it is a multi-...
Development of a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI)

Satellite-observed radiance is a nonlinear functional of surface properties and atmospheric temperature and absorbing gas profiles as described by the radiative transfer equation (RTE). In the era of hyperspectral sounders with thousands of high-...
SIMD Monte-Carlo Numerical Simulations Accelerated on GPU and Xeon Phi

The efficiency of a pleasingly parallel application is studied for several computing platforms. A real world problem, i.e., Monte-Carlo numerical simulations of stratospheric balloon envelope drift descent is considered. We detail the optimization of ...

Comments

Information & Contributors

Information

Published In

HPCAsia '21: The International Conference on High Performance Computing in Asia-Pacific Region

January 2021

143 pages

ISBN:9781450388429

DOI:10.1145/3432261

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 January 2021

Check for updates

Author Tags

Qualifiers

Poster
Research
Refereed limited

Conference

HPC Asia 2021

HPC Asia 2021: The International Conference on High Performance Computing in Asia-Pacific Region

January 20 - 22, 2021

Virtual Event, Republic of Korea

Acceptance Rates

Overall Acceptance Rate 69 of 143 submissions, 48%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
72
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)0

Reflects downloads up to 17 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Bishnoi AStein OMeyer CRedler REicker NHaak HHoffmann LKlocke DKornblueh LSuarez E(2024)Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rcGeoscientific Model Development10.5194/gmd-17-261-202417:1(261-273)Online publication date: 12-Jan-2024
https://doi.org/10.5194/gmd-17-261-2024
Sophocleous KChristoudias T(2022)Reduced-Precision Chemical Kinetics in Atmospheric ModelsAtmosphere10.3390/atmos1309141813:9(1418)Online publication date: 2-Sep-2022
https://doi.org/10.3390/atmos13091418

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Abstract

References

Cited By

Index Terms

Recommendations

Architecture-Aware Mapping and Optimization on a 1600-Core GPU

Development of a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI)

SIMD Monte-Carlo Numerical Simulations Accelerated on GPU and Xeon Phi

Comments

Information

Published In

Publisher

Publication History

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

HTML Format

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations