research-article

Parallel time-space processing model based fast N-body simulation on GPUs

Authors:

Guosun ZengAuthors Info & Claims

PMAM '13: Proceedings of the 2013 International Workshop on Programming Models and Applications for Multicores and Manycores

Pages 63 - 69

https://doi.org/10.1145/2442992.2442999

Published: 23 February 2013 Publication History

Get Access

Abstract

The N-body problems simulate the evolution of a system of N bodies where the force exerted on each body arises due to its interaction with all the other bodies in the system. In this paper, we present a novel parallel implementation of N-body gravitational simulation on GPUs. We analyze the current implementation of GPU, and give our new method on implementing N-body algorithm on HD Radeon 5870 GPU of AMD. The experimental results show that this method achieves an acceleration of 413 compared with CPU, and an acceleration up to 5.5 times compared with other GPU based methods.

References

[1]

J. Barnes and P. Hut. O(nlogn) force-calculation algorithm. Nature, 324: 446--449, 1986.

Crossref

Google Scholar

[2]

L. Greengard and V. Rokhlin. A fast algorithm for particle simulations, Journal of Computational Physics, 73(2): 325--348, 1987.

Digital Library

Google Scholar

[3]

T. Hamada and I. Titaka. The chamomile scheme: an optimized algorithm for n-body simulations on programmable graphics processing units. arXiv:astro-ph/0703100v1, 2007.

Google Scholar

[4]

L. Nyland, M. Harris, J. Prins. Fast n-body simulation with CUDA. GPU germs, 2007, 3:677--695.

Google Scholar

[5]

R. G. Belleman, J. Bedorf, and S. F. Portegies Zwart. High performance direct gravitational n-body simulations on graphics processing units ii: An implementation in cuda. New Astronomy, 13:103--112,2008.

Crossref

Google Scholar

[6]

T. Hamada, K. Nitadori, K. Benkrid, etl. A novel multiple-walk parallel algorithm for the Barnes--Hut treecode on GPUs -- towards cost effective, high performance N-body simulation. Computer Science - Research and Development, 2009, 24:21--31.

Crossref

Google Scholar

[7]

E. Gaburov, S. Harfst, and S. Portegies Zwart. Sapporo: A way to turn your graphics cards into a grape-6. New Astronomy, 14:630--637, 2009.

Crossref

Google Scholar

[8]

M. J. Stock and A. Gharakhani. Toward efficient gpu-accelerated n-body simulations. AIAA Paper, 2008--608, 46th AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada, Jan. 7 - 10:1--13, 2008.

Crossref

Google Scholar

[9]

N. A. Gumerov and R. Duraiswami. Fast multipole methods on graphics processors. Journal of Computational Physics, 227:8290--8313, 2008.

Digital Library

Google Scholar

[10]

T. Hamada, R. Yokota, K. Nitadori, T. Narumi, K. Yasuoka, M. Taiji. 42 TFLops hierarchical n-body simulations on GPUs with applications in both astrophysics and turbulence. SC09, Nov. 2009, pp:14--20.

Digital Library

Google Scholar

Cited By

View all

Grasso IPellegrini SCosenza BFahringer T(2019)A uniform approach for programming distributed heterogeneous computing systemsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2014.08.00274:12(3228-3239)Online publication date: 4-Jan-2019
https://dl.acm.org/doi/10.1016/j.jpdc.2014.08.002

Index Terms

Parallel time-space processing model based fast N-body simulation on GPUs

Recommendations

A sparse octree gravitational N-body code that runs entirely on the GPU processor

We present the implementation and performance of a new gravitational N-body tree-code that is specifically designed for the graphics processing unit (GPU).1The code is publicly available at: http://castle.strw.leidenuniv.nl/software.html.1 All parts of ...
Gillespie's Stochastic Simulation Algorithm on MIC coprocessors

To investigate the behavior of biochemical systems, many runs of Gillespie's Stochastic Simulation Algorithm (SSA) are generally needed, causing excessive computational costs on Central Processing Units (CPUs). Since all SSA runs are independent, the ...
Direct N-body Kernels for Multicore Platforms
ICPP '09: Proceedings of the 2009 International Conference on Parallel Processing

We present an inter-architectural comparison of single-and double-precision direct n-body implementations on modern multicore platforms, including those based on the Intel Nehalem and AMD Barcelona systems, the Sony-Toshiba-IBM PowerXCell/8i processor, ...

Comments

Information & Contributors

Information

Published In

PMAM '13: Proceedings of the 2013 International Workshop on Programming Models and Applications for Multicores and Manycores

February 2013

134 pages

ISBN:9781450319089

DOI:10.1145/2442992

Editors:
Pavan Balaji
Argonne National Laboratory
,
Minyi Guo
Shanghai Jiao Tong University, China
,
Zhiyi Huang
University of Otago, New Zealand

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 February 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Open Project Program of the National Laboratory of Pattern Recognition (NLPR)
Fundamental Research Funds for the Central Universities
Open Project Program of the State Key Lab of CAD&CG, Zhejiang University
Ph.D. Programs Foundation of Ministry of Education
National Natural Science Foundation of China
Program of Shanghai Subject Chief Scientist
Ministry of Science and Technology of the People's Republic of China
Microsoft Research

Conference

PPoPP '13

Sponsor:

SIGPLAN

PPoPP '13: ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

February 23, 2013

Guangdong, Shenzhen, China

Acceptance Rates

Overall Acceptance Rate 53 of 97 submissions, 55%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
131
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)0

Reflects downloads up to 28 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Grasso IPellegrini SCosenza BFahringer T(2019)A uniform approach for programming distributed heterogeneous computing systemsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2014.08.00274:12(3228-3239)Online publication date: 4-Jan-2019
https://dl.acm.org/doi/10.1016/j.jpdc.2014.08.002

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

Abstract

References

Cited By

Index Terms

Recommendations

A sparse octree gravitational N-body code that runs entirely on the GPU processor

Gillespie's Stochastic Simulation Algorithm on MIC coprocessors

Direct N-body Kernels for Multicore Platforms

Comments

Information

Published In

Sponsors

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Funding Sources

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations