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Global Grid of Grapes

Derek Groen
Derek Groen
Derek GroenLecturer in Simulation and Modelling at Brunel University London, visiting Lecturer@UCL

This is the first poster I presented as part of my PhD. It focuses on executing N-body simulations using GRAPE specialized hardware on machines in different continents.

Global Grid of Grapes

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Simulating Star Clusters onSimulating Star Clusters on
a Global Grid of GRAPEsa Global Grid of GRAPEs
Derek Groen a,b
, Simon Portegies Zwart a,b
, Steve McMillan c
, Jun Makino d
a
Section Computational Science, University of Amsterdam, The Netherlands
b
Astronomical Institute “Anton Pannekoek”, University of Amsterdam, The Netherlands
c
Drexel University, Philadelphia, United States,
d
University of Tokyo, Tokyo, Japan
Abstract
We present performance results of N-
body simulation on the Grid. Our
world-wide testbed consists of one
GRAPE-6 in Tokyo, one in Philadelphia
and one in Amsterdam. Based on
these results we construct a perfor-
mance model, and apply it to predict
the performance of a grid consisting
of all 1115 GRAPEs in existence.
Background
Star clusters are often simulated using direct-
method N-body integrators. These simulations
calculate the gravitational force interactions
between all stars. Specialized hardware solutions
such as GRAvity PipEs [1] greatly accelerate N-
body simulations by computing force interactions
for multiple stars simultaneously. Using GRAPEs in
parallel allows for even faster calculations [2].
Grid technology provides a convenient and secure
wide area computing environment [3], and enables
the use of GRAPEs from different institutions in
parallel. We use the grid to execute one N-body
simulation in parallel over several GRAPEs located
world-wide. We analyze the performance of a
simulation on our grid of GRAPEs, construct a
performance model, and apply this model to
predict the performance using all GRAPEs on the
planet.
Results
We measured the execution time of our simulation
across 3 sites (Amsterdam, Philadelphia and
Tokyo). Parallel GRAPE runs are generally slower
due to communication, but the performance
penalty diminishes for larger N, as more time is
spent on force calculations. We expect that around
1 million particles, our grid simulation will run
faster than a simulation using 1 GRAPE.
Prediction
We have applied our performance model to
predict the obtained speedup for a hypothetical
grid of all 1115 GRAPEs (given by the black
dashed line), as compared to a single PC.
Conclusion
Organizing all the major GRAPEs on the planet is
probably not worth the effort, due to the cost of
network communication. However, organizing
large GRAPE sites within one continent appears
politically doable and computationally favorable.
References & Acknowledgements
1. Makino et.. al., GRAPE-6: Massively-Parallel Special-Purpose Computer for Astrophysical Particle
Simulations. Publications of the Astronomical Society of Japan 55, 1163-1187.
2. Harfst et. al., Performance analysis of direct N-body algorithms on special-purpose
supercomputers. New Astronomy 12, 357-377.
3. Foster et. al., The Anatomy of the Grid: Enabling Scalable Virtual Organizations. International
Journal of High Performance Computing Applications 15 (3), 200-222.
This research is supported by NWO grant for the D2G2 project
(#643.200.503) and by the European Commission grant for the
QosCosGrid project (FP6-2005-IST-5 033883).
See arXiv:0709.4552 for the full article.

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Global Grid of Grapes

  • 1. Simulating Star Clusters onSimulating Star Clusters on a Global Grid of GRAPEsa Global Grid of GRAPEs Derek Groen a,b , Simon Portegies Zwart a,b , Steve McMillan c , Jun Makino d a Section Computational Science, University of Amsterdam, The Netherlands b Astronomical Institute “Anton Pannekoek”, University of Amsterdam, The Netherlands c Drexel University, Philadelphia, United States, d University of Tokyo, Tokyo, Japan Abstract We present performance results of N- body simulation on the Grid. Our world-wide testbed consists of one GRAPE-6 in Tokyo, one in Philadelphia and one in Amsterdam. Based on these results we construct a perfor- mance model, and apply it to predict the performance of a grid consisting of all 1115 GRAPEs in existence. Background Star clusters are often simulated using direct- method N-body integrators. These simulations calculate the gravitational force interactions between all stars. Specialized hardware solutions such as GRAvity PipEs [1] greatly accelerate N- body simulations by computing force interactions for multiple stars simultaneously. Using GRAPEs in parallel allows for even faster calculations [2]. Grid technology provides a convenient and secure wide area computing environment [3], and enables the use of GRAPEs from different institutions in parallel. We use the grid to execute one N-body simulation in parallel over several GRAPEs located world-wide. We analyze the performance of a simulation on our grid of GRAPEs, construct a performance model, and apply this model to predict the performance using all GRAPEs on the planet. Results We measured the execution time of our simulation across 3 sites (Amsterdam, Philadelphia and Tokyo). Parallel GRAPE runs are generally slower due to communication, but the performance penalty diminishes for larger N, as more time is spent on force calculations. We expect that around 1 million particles, our grid simulation will run faster than a simulation using 1 GRAPE. Prediction We have applied our performance model to predict the obtained speedup for a hypothetical grid of all 1115 GRAPEs (given by the black dashed line), as compared to a single PC. Conclusion Organizing all the major GRAPEs on the planet is probably not worth the effort, due to the cost of network communication. However, organizing large GRAPE sites within one continent appears politically doable and computationally favorable. References & Acknowledgements 1. Makino et.. al., GRAPE-6: Massively-Parallel Special-Purpose Computer for Astrophysical Particle Simulations. Publications of the Astronomical Society of Japan 55, 1163-1187. 2. Harfst et. al., Performance analysis of direct N-body algorithms on special-purpose supercomputers. New Astronomy 12, 357-377. 3. Foster et. al., The Anatomy of the Grid: Enabling Scalable Virtual Organizations. International Journal of High Performance Computing Applications 15 (3), 200-222. This research is supported by NWO grant for the D2G2 project (#643.200.503) and by the European Commission grant for the QosCosGrid project (FP6-2005-IST-5 033883). See arXiv:0709.4552 for the full article.