Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/31362
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | NEMETH, Balazs | - |
dc.contributor.author | HABER, Tom | - |
dc.contributor.author | LIESENBORGS, Jori | - |
dc.contributor.author | LAMOTTE, Wim | - |
dc.date.accessioned | 2020-07-01T11:49:35Z | - |
dc.date.available | 2020-07-01T11:49:35Z | - |
dc.date.issued | 2020 | - |
dc.date.submitted | 2020-06-29T10:54:40Z | - |
dc.identifier.citation | Computational Science – ICCS 2020, p. 161 -174 | - |
dc.identifier.isbn | 978-3-030-50370-3 | - |
dc.identifier.isbn | 978-3-030-50371-0 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://hdl.handle.net/1942/31362 | - |
dc.description.abstract | Hierarchical models describe phenomena by grouping data into multiple levels. Due to the size of these models, parallel execution is required to avoid prohibitively long computing time. While it is occasionally possible to specify some of these models using parallel building blocks, this limits expressivity. Therefore, a more general generative specification is preferred. To leverage parallel computing capacity, these specifications can be annotated, but doing so effectively assumes that the modeler has expertise from computer science. This paper outlines how to identify parallel parts automatically by leveraging the conditional independence property in the graphical model extracted from the dataflow graph of model specifications. Computation related to random variables with the same depth in the graphical model are identified as candidates for parallel execution. Since subsequent proposals in the parameter space exploration of the model are clustered together, the results show that the well known longest processing time scheduling heuristic deals adequately with load imbalance. The proposed parallelization is evaluated on two pharmacometrics models, a domain where hierarchical models with load imbalance are common due to the numeric simulation of pharmacokinet-ics and pharmacodynamics of human subjects. The varying number of measurements taken per subject further exacerbates load imbalance. | - |
dc.description.sponsorship | Acknowledgments Part of the work presented in this paper was funded by Johnson & Johnson. | - |
dc.language.iso | en | - |
dc.relation.ispartofseries | Lecture Notes in Computer Science | - |
dc.rights | Springer Nature Switzerland AG 2020 | - |
dc.subject.other | High performance computing | - |
dc.subject.other | Descriptive language | - |
dc.subject.other | Probabilistic modelling | - |
dc.subject.other | Automatic parallelization | - |
dc.subject.other | Dataflow | - |
dc.subject.other | Hierarchical models | - |
dc.title | From Conditional Independence to Parallel Execution in Hierarchical Models | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.conferencedate | 3-5 June 2020 | - |
local.bibliographicCitation.conferencename | International Conference on Computational Science | - |
local.bibliographicCitation.conferenceplace | Amsterdam | - |
dc.identifier.epage | 174 | - |
dc.identifier.spage | 161 | - |
local.bibliographicCitation.jcat | C1 | - |
local.type.refereed | Refereed | - |
local.type.specified | Proceedings Paper | - |
local.relation.ispartofseriesnr | 12137 | - |
local.type.programme | VSC | - |
dc.identifier.doi | 10.1007/978-3-030-50371-0_12 | - |
dc.identifier.eissn | 1611-3349 | - |
local.provider.type | CrossRef | - |
local.bibliographicCitation.btitle | Computational Science – ICCS 2020 | - |
local.uhasselt.uhpub | yes | - |
local.uhasselt.international | no | - |
item.fulltext | With Fulltext | - |
item.contributor | NEMETH, Balazs | - |
item.contributor | HABER, Tom | - |
item.contributor | LIESENBORGS, Jori | - |
item.contributor | LAMOTTE, Wim | - |
item.accessRights | Restricted Access | - |
item.validation | vabb 2022 | - |
item.fullcitation | NEMETH, Balazs; HABER, Tom; LIESENBORGS, Jori & LAMOTTE, Wim (2020) From Conditional Independence to Parallel Execution in Hierarchical Models. In: Computational Science – ICCS 2020, p. 161 -174. | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Nemeth2020_Chapter_FromConditionalIndependenceToP.pdf Restricted Access | Published version | 397.61 kB | Adobe PDF | View/Open Request a copy |
Page view(s)
52
checked on Sep 7, 2022
Download(s)
38
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.