Single Node On-Line Simulation of MPI Applications with SMPI
File(s)stillwell_ccgrid2009.pdf (434.11 KB)
Accepted version
Author(s)
Type
Conference Paper
Abstract
Simulation is a popular approach for predicting the performance of MPI applications for platforms that are not at one’s disposal. It is also a way to teach the principles
of parallel programming and high-performance computing to students without access to a parallel computer. In this work we present SMPI, a simulator for MPI applications that uses on-line simulation, i.e., the application is executed but part of the execution takes place within a simulation component. SMPI simulations account for network contention in a fast and scalable manner. SMPI also implements an original and validated piece-wise linear model for data transfer times between cluster nodes.
Finally SMPI simulations of large-scale applications on large-scale platforms can be executed on a single node thanks to techniques to reduce the simulation’s compute time and memory footprint. These contributions are validated via a large set
of experiments in which SMPI is compared to popular MPI implementations with a view to assess its accuracy, scalability, and speed.
of parallel programming and high-performance computing to students without access to a parallel computer. In this work we present SMPI, a simulator for MPI applications that uses on-line simulation, i.e., the application is executed but part of the execution takes place within a simulation component. SMPI simulations account for network contention in a fast and scalable manner. SMPI also implements an original and validated piece-wise linear model for data transfer times between cluster nodes.
Finally SMPI simulations of large-scale applications on large-scale platforms can be executed on a single node thanks to techniques to reduce the simulation’s compute time and memory footprint. These contributions are validated via a large set
of experiments in which SMPI is compared to popular MPI implementations with a view to assess its accuracy, scalability, and speed.
Date Issued
2011-05-20
Date Acceptance
2011-05-16
Citation
Proceedings of the 25th IEEE International Parallel and Distributed Processing Symposium, 2011, pp.664-675
ISBN
978-1-61284-372-8
ISSN
1530-2075
Publisher
IEEE
Start Page
664
End Page
675
Journal / Book Title
Proceedings of the 25th IEEE International Parallel and Distributed Processing Symposium
Copyright Statement
© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
25th IEEE International Parallel and Distributed Processing Symposium
Publication Status
Published
Start Date
2011-05-16
Finish Date
2011-05-20
Coverage Spatial
Anchorage, Alaska, USA