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Sökning: id:"swepub:oai:DiVA.org:liu-5720" > Automatic Paralleli...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00003694nam a2200397 4500
001oai:DiVA.org:liu-5720
003SwePub
008030415s2002 | |||||||||||000 ||eng|
020 a 917373280Xq print
024a https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-57202 URI
040 a (SwePub)liu
041 a engb eng
042 9 SwePub
072 7a vet2 swepub-contenttype
072 7a lic2 swepub-publicationtype
100a Aronsson, Peteru Linköpings universitet,PELAB - Laboratoriet för programmeringsomgivningar,Tekniska högskolan4 aut0 (Swepub:liu)petar73
2451 0a Automatic Parallelization of Simulation Code from Equation Based Simulation Languages
264 1b Institutionen för datavetenskap,c 2002
300 a 107 s.
338 a electronic2 rdacarrier
490a Linköping Studies in Science and Technology. Thesis,x 0280-7971 ;v 933
500 a Report code: LiU-Tek-Lic-2002:06.
520 a Modern state-of-the-art equation based object oriented modeling languages such as Modelica have enabled easy modeling of large and complex physical systems. When such complex models are to be simulated, simulation tools typically perform a number of optimizations on the underlying set of equations in the modeled system, with the goal of gaining better simulation performance by decreasing the equation system size and complexity. The tools then typically generate efficient code to obtain fast execution of the simulations. However, with increasing complexity of modeled systems the number of equations and variables are increasing. Therefore, to be able to simulate these large complex systems in an efficient way parallel computing can be exploited.This thesis presents the work of building an automatic parallelization tool that produces an efficient parallel version of the simulation code by building a data dependency graph (task graph) from the simulation code and applying efficient scheduling and clustering algorithms on the task graph. Various scheduling and clustering algorithms, adapted for the requirements from this type of simulation code, have been implemented and evaluated. The scheduling and clustering algorithms presented and evaluated can also be used for functional dataflow languages in general, since the algorithms work on a task graph with dataflow edges between nodes.Results are given in form of speedup measurements and task graph statistics produced by the tool. The conclusion drawn is that some of the algorithms investigated and adapted in this work give reasonable measured speedup results for some specific Modelica models, e.g. a model of a thermofluid pipe gave a speedup of about 2.5 on 8 processors in a PC-cluster. However, future work lies in finding a good algorithm that works well in general.
650 7a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe
650 7a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng
653 a state-of-the-art equation
653 a object oriented modeling
653 a automatic parallelization tool
653 a data dependency graph
653 a clustering algorithms
653 a Computer science
653 a Datavetenskap
700a Fritzson, Peteru Linköpings universitet,PELAB - Laboratoriet för programmeringsomgivningar,Tekniska högskolan4 ths0 (Swepub:liu)petfr27
710a Linköpings universitetb PELAB - Laboratoriet för programmeringsomgivningar4 org
856u https://liu.diva-portal.org/smash/get/diva2:21475/FULLTEXT01.pdfx primaryx Raw objecty fulltext
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5720

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Aronsson, Peter
Fritzson, Peter
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NATURVETENSKAP
NATURVETENSKAP
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och Datavetenskap
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