Title
Performance Analysis of a High Energy Colliding Beam Simulation Code on Four HPC Architectures
Abstract
The high energy colliders are essential to study the inner structure of nuclear and elementary particles. A parallel particle simulation code, BeamBeam3D, has been developed and actively used to model the beam dynamics and to optimize the performance of these colliders. In this paper, we analyzed the performance characteristics of BeamBeam3D on four leading high performance computing architectures, including a massive parallel system, a commodity-based cluster, an advanced vector platform, and a novel architecture focused on low power consumption and high density. We examine how to partition the workload among the processors to effectively use the computing resources, whether these platforms exhibit similar performance bottlenecks and how to address them, whether some platforms perform substantially better than others, and finally, the implications of BeamBeam3D for the design of the next generation supercomputer architectures
Year
DOI
Venue
2006
10.1109/ICPP.2006.59
ICPP
Keywords
Field
DocType
parallel particle simulation code,computing resource,low power consumption,leading high performance computing,beambeam3d,physics computing,elementary particle,parallel architectures,supercomputer architecture,massive parallel system,multiprocessing systems,high energy colliding beam simulation code,high density,beam dynamic,nuclear particle,commodity-based cluster,high energy colliding beam,high performance computing architecture,simulation code,advanced vector platform,performance analysis,similar performance bottleneck,hpc architecture,performance characteristic,beam dynamics,nuclear physics,high energy colliders,hpc architectures,elementary particles
Supercomputer architecture,Supercomputer,Workload,Computer science,Parallel computing,High density,Beam (structure),High energy,Collider,Power consumption
Conference
ISSN
ISBN
Citations 
0190-3918
0-7695-2636-5
0
PageRank 
References 
Authors
0.34
9
4
Name
Order
Citations
PageRank
Hongzhang Shan144545.98
Ji Qiang27910.07
Erich Strohmaier328435.26
Katherine A. Yelick43494407.23