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dc.contributor.authorTaura, Kenjiro
dc.contributor.authorNakashima, Jun
dc.contributor.authorYokota, Rio
dc.contributor.authorMaruyama, Naoya
dc.date.accessioned2015-08-04T07:05:23Z
dc.date.available2015-08-04T07:05:23Z
dc.date.issued2012-11
dc.identifier.isbn9780769549569
dc.identifier.doi10.1109/SC.Companion.2012.86
dc.identifier.urihttp://hdl.handle.net/10754/564624
dc.description.abstractThis paper describes a task parallel implementation of ExaFMM, an open source implementation of fast multipole methods (FMM), using a lightweight task parallel library MassiveThreads. Although there have been many attempts on parallelizing FMM, experiences have almost exclusively been limited to formulation based on flat homogeneous parallel loops. FMM in fact contains operations that cannot be readily expressed in such conventional but restrictive models. We show that task parallelism, or parallel recursions in particular, allows us to parallelize all operations of FMM naturally and scalably. Moreover it allows us to parallelize a ''mutual interaction'' for force/potential evaluation, which is roughly twice as efficient as a more conventional, unidirectional force/potential evaluation. The net result is an open source FMM that is clearly among the fastest single node implementations, including those on GPUs; with a million particles on a 32 cores Sandy Bridge 2.20GHz node, it completes a single time step including tree construction and force/potential evaluation in 65 milliseconds. The study clearly showcases both programmability and performance benefits of flexible parallel constructs over more monolithic parallel loops. © 2012 IEEE.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectdivide and conquer
dc.subjectExaFMM
dc.subjectfast multipole methods
dc.subjectFMM
dc.subjectMassiveThreads
dc.subjecttask parallelism
dc.titleA task parallel implementation of fast multipole methods
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentExtreme Computing Research Center
dc.identifier.journal2012 SC Companion: High Performance Computing, Networking Storage and Analysis
dc.conference.date10 November 2012 through 16 November 2012
dc.conference.name2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012
dc.conference.locationSalt Lake City, UT
dc.contributor.institutionGraduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
dc.contributor.institutionRIKEN Advanced Institute for Computational Science, 7-1-26 Minatojima-minami-machi, Chuo-ku Kobe, Hyogo 650-0047, Japan
kaust.personYokota, Rio


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