uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Sampled Simulation of Task-Based Programs
Barcelona Supercomp Ctr, Barcelona 08034, Spain;Rhein Westfal TH Aachen, D-52062 Aachen, Germany.
NUS, Singapore 119077, Singapore.
Arm Ltd, Austin, TX 78735 USA.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.ORCID iD: 0000-0003-2314-7307
Show others and affiliations
2019 (English)In: I.E.E.E. transactions on computers (Print), ISSN 0018-9340, E-ISSN 1557-9956, Vol. 68, no 2, p. 255-269Article in journal (Refereed) Published
Abstract [en]

Sampled simulation is a mature technique for reducing simulation time of single-threaded programs. Nevertheless, current sampling techniques do not take advantage of other execution models, like task-based execution, to provide both more accurate and faster simulation. Recent multi-threaded sampling techniques assume that the workload assigned to each thread does not change across multiple executions of a program. This assumption does not hold for dynamically scheduled task-based programming models. Task-based programming models allow the programmer to specify program segments as tasks which are instantiated many times and scheduled dynamically to available threads. Due to variation in scheduling decisions, two consecutive executions on the same machine typically result in different instruction streams processed by each thread. In this paper, we propose TaskPoint, a sampled simulation technique for dynamically scheduled task-based programs. We leverage task instances as sampling units and simulate only a fraction of all task instances in detail. Between detailed simulation intervals, we employ a novel fast-forwarding mechanism for dynamically scheduled programs. We evaluate different automatic techniques for clustering task instances and show that DBSCAN clustering combined with analytical performance modeling provides the best trade-off of simulation speed and accuracy. TaskPoint is the first technique combining sampled simulation and analytical modeling and provides a new way to trade off simulation speed and accuracy. Compared to detailed simulation, TaskPoint accelerates architectural simulation with 8 simulated threads by an average factor of 220x at an average error of 0.5 percent and a maximum error of 7.9 percent.

Place, publisher, year, edition, pages
IEEE COMPUTER SOC , 2019. Vol. 68, no 2, p. 255-269
Keywords [en]
Sampled simulation, task-based, analytical performance modeling
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-376810DOI: 10.1109/TC.2018.2860012ISI: 000456176200008OAI: oai:DiVA.org:uu-376810DiVA, id: diva2:1291056
Funder
EU, Horizon 2020, 687698EU, European Research Council, GA 321253EU, FP7, Seventh Framework Programme, 2013BP B 00243Available from: 2019-02-22 Created: 2019-02-22 Last updated: 2019-02-22Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Ceballos, Germán

Search in DiVA

By author/editor
Ceballos, Germán
By organisation
Computer Systems
In the same journal
I.E.E.E. transactions on computers (Print)
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 11 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf