University of Limerick Institutional Repository

Heterogeneous multiconstraint application partitioner (HMAP)

DSpace Repository

Show simple item record

dc.contributor.author Muralidharan, Servesh
dc.contributor.author Vasudevan, Aravind
dc.contributor.author Malik, Avinash
dc.contributor.author Gregg, David
dc.date.accessioned 2014-02-07T15:05:43Z
dc.date.available 2014-02-07T15:05:43Z
dc.date.issued 2013
dc.identifier.uri http://hdl.handle.net/10344/3664
dc.description peer-reviewed en_US
dc.description.abstract In this article we propose a novel framework – Heterogeneous Multiconstraint Application Partitioner (HMAP) for exploiting parallelism on heterogeneous High performance computing (HPC) architectures. Given a heterogeneous HPC cluster with varying compute units, communication constraints and topology, HMAP framework can be utilized for partitioning applications exhibiting task and data parallelism resulting in increased performance. The challenge lies in the fact that heterogeneous compute clusters consist of processing elements exhibiting different compute speeds, vector lengths, and communication bandwidths, which all need to be considered when partitioning the application and associated data. We tackle this problem using a staged graph partitioning approach. Experimental evaluation on a variety of different heterogeneous HPC clusters and applications show that our framework can exploit parallelism resulting in more than 3 speedup over current state of the art partitioning technique. HMAP framework finishes within seconds even for architectures with 100’s of processing elements, which makes our algorithm suitable for exploring parallelism potential. en_US
dc.language.iso eng en_US
dc.publisher IEEE Computer Society en_US
dc.relation.ispartofseries 11th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA-13);pp. 999-1007
dc.relation.uri http://dx.doi.org/10.1109/TrustCom.2013.122
dc.rights “© 2013 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.” en_US
dc.subject graph partitioning en_US
dc.subject vectorization en_US
dc.subject data parallelism en_US
dc.subject heterogeneous architectures en_US
dc.subject clusters en_US
dc.title Heterogeneous multiconstraint application partitioner (HMAP) en_US
dc.type info:eu-repo/semantics/conferenceObject en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.contributor.sponsor IRCSET en_US
dc.contributor.sponsor IBM en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search ULIR


Browse

My Account

Statistics