Load balancing for hierarchical grid computing: a case study

Authors:
Chunxi Chen;Bertil Schmidt
Affiliations:
School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore
Venue:
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
Year:
2004

Citing 9
Cited 0

A time-efficient, linear-space local similarity algorithm

Advances in Applied Mathematics
MagPIe: MPI's collective communication operations for clustered wide area systems

Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
A linear space algorithm for computing maximal common subsequences

Communications of the ACM
Parallel implementation and performance of fastDNAml: a program for maximum likelihood phylogenetic inference

Proceedings of the 2001 ACM/IEEE conference on Supercomputing
An Architecture of Stampi: MPI Library on a Cluster of Parallel Computers

Proceedings of the 7th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Distributed Computing in a Heterogeneous Computing Environment

Proceedings of the 5th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Grid enabled MPI solutions for Clusters

CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
The Grid 2: Blueprint for a New Computing Infrastructure

The Grid 2: Blueprint for a New Computing Infrastructure
Performance analysis of computational biology applications on hierarchical Grid systems

CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid

Quantified Score

Hi-index	0.00

Visualization

Abstract

Hierarchical grid computing is a way to gain high compute power at low cost by combining existing computational resources instead of building a new one It typically has heterogeneous characteristics, such as: (1) Resources have different computational power; and (2) Resources are shared among users; and (3) Resources are usually connected by networks with widely varying performance characteristics This makes the development or adaptation of parallel applications on hierarchical grids challenging In this paper, we study three load balancing techniques for hierarchical grids: static load balancing, master-slave and a new technique called “scheduler-worker” We evaluate the performance of these techniques for computing the alignment of long DNA sequences on a grid.