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Munasinghe, Kalyani
Publications (4 of 4) Show all publications
Munasinghe, K. & Wait, R. (2006). Study of load balancing strategies for finite element computations on heterogeneous clusters. In: Applied Parallel Computing: State of the Art in Scientific Computing (pp. 1123-1130). Berlin: Springer-Verlag
Open this publication in new window or tab >>Study of load balancing strategies for finite element computations on heterogeneous clusters
2006 (English)In: Applied Parallel Computing: State of the Art in Scientific Computing, Berlin: Springer-Verlag , 2006, p. 1123-1130Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Berlin: Springer-Verlag, 2006
Series
Lecture Notes in Computer Science ; 3732
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-80676 (URN)10.1007/11558958_135 (DOI)000237003200135 ()
Available from: 2008-03-08 Created: 2008-03-08 Last updated: 2018-01-13Bibliographically approved
Munasinghe, K. & Wait, R. (2005). Load balancing by changing the graph connectivity on heterogeneous clusters. In: Advances in Grid Computing – EGC 2005 (pp. 1040-1047). Berlin: Springer-Verlag
Open this publication in new window or tab >>Load balancing by changing the graph connectivity on heterogeneous clusters
2005 (English)In: Advances in Grid Computing – EGC 2005, Berlin: Springer-Verlag , 2005, p. 1040-1047Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Berlin: Springer-Verlag, 2005
Series
Lecture Notes in Computer Science ; 3470
National Category
Computer Sciences
Identifiers
urn:nbn:se:uu:diva-72075 (URN)10.1007/11508380_106 (DOI)
Available from: 2007-01-25 Created: 2007-01-25 Last updated: 2018-01-10Bibliographically approved
Munasinghe, K. & Wait, R. (2002). Load balancing in scientific computing on clusters. In: Proc. Int. Workshop on Grid and Cooperative Computing (pp. 281-288). Beijing, China: Publishing House of Electronics Industry
Open this publication in new window or tab >>Load balancing in scientific computing on clusters
2002 (English)In: Proc. Int. Workshop on Grid and Cooperative Computing, Beijing, China: Publishing House of Electronics Industry , 2002, p. 281-288Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Beijing, China: Publishing House of Electronics Industry, 2002
National Category
Computer Sciences
Identifiers
urn:nbn:se:uu:diva-18868 (URN)
Available from: 2006-12-11 Created: 2006-12-11 Last updated: 2018-01-12Bibliographically approved
Munasinghe, K. (2002). On using mobile agents for load balancing in high performance computing. (Licentiate dissertation). Uppsala University
Open this publication in new window or tab >>On using mobile agents for load balancing in high performance computing
2002 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

One recent advance in software technology is the development of software agents that can adapt to changes in their environment and can cooperate and coordinate their activities to complete a given task. Such agents can be distributed over a network.

Advances in hardware technology have meant that clusters of workstations can be used to create parallel virtual machines that bring the power of parallel computing to a much wider research and development community. Many software packages are now being developed to utilise such cluster environments.

In a cluster, each processor will be multitasking and running other jobs simultaneously with a distributed application that uses a message passing environment such as MPI. A typical application might be a large scale mesh-based computation, such as a finite element code, in which load balancing is equivalent to mesh partitioning. When the load is varying between processors within the cluster, distributing the computation in equal amounts may not deliver the optimum performance. Some machines may be very heavily loaded by other users while other processors may have no such additional load. It may be beneficial to measure current system information and use this information when balancing the load within a single distributed application program.

This thesis presents one approach to distributing workload more efficiently in a multi-user distributed environment by using mobile agents to collect system information which is then transmitted to all the MPI tasks. The thesis contains a review of software agents and mesh partitioning together with some numerical experiments and a paper.

Place, publisher, year, edition, pages
Uppsala University, 2002
Series
Information technology licentiate theses: Licentiate theses from the Department of Information Technology, ISSN 1404-5117 ; 2002-006
National Category
Software Engineering
Research subject
Scientific Computing
Identifiers
urn:nbn:se:uu:diva-86391 (URN)
Supervisors
Available from: 2002-06-07 Created: 2007-01-25 Last updated: 2018-01-13Bibliographically approved
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