Grid resource selection by application benchmarking for computational haemodynamics applications

Authors:
Alfredo Tirado-Ramos;George Tsouloupas;Marios Dikaiakos;Peter Sloot
Affiliations:
Faculty of Sciences, Section Computational Science, University of Amsterdam, Amsterdam, The Netherlands;Department of Computer Science, University of Cyprus, Nicosia, Cyprus;Department of Computer Science, University of Cyprus, Nicosia, Cyprus;Faculty of Sciences, Section Computational Science, University of Amsterdam, Amsterdam, The Netherlands
Venue:
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
Year:
2005

Citing 5
Cited 4

Specifying resources and services in metacomputing environments

Parallel Computing - Special issue on applications
Enabling Technologies for Computational Science: Frameworks, Middleware and Environments

Enabling Technologies for Computational Science: Frameworks, Middleware and Environments
Data Management in an International Data Grid Project

GRID '00 Proceedings of the First IEEE/ACM International Workshop on Grid Computing
GridBench: A Tool for Benchmarking Grids

GRID '03 Proceedings of the 4th International Workshop on Grid Computing
An integrative approach to high-performance biomedical problem solving environments on the Grid

Parallel Computing - Special issue: High-performance parallel bio-computing

A Report on the Effect of Heterogeneity of the Grid Environment on a Grid Job

Large-Scale Scientific Computing
A Hybrid Intelligent Method for Performance Modeling and Prediction of Workflow Activities in Grids

CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Exploiting performance characterization of BLAST in the grid

Cluster Computing
Grid resource ranking using low-level performance measurements

Euro-Par'07 Proceedings of the 13th international Euro-Par conference on Parallel Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Grid benchmarking for improved computational resource selection can shed a light for improving the performance of computationally intensive applications. In this paper we report on a number of experiments with a biomedical parallel application to investigate the levels of performance offered by hardware resources distributed across a pan-European computational Grid network. We provide a number of performance measurements based on the iteration time per processor and communication delay between processors, for a blood flow simulation benchmark based on the lattice Boltzmann method. We have found that the performance results obtained from real application benchmarking are much more useful for running our biomedical application on a highly distributed grid infrastructure than the regular resource information provided by standard Grid information services to resource brokers.