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
Spatial and Temporal Cache Sharing Analysis in Tasks
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. (Uppsala Architecture Research Team)ORCID iD: 0000-0003-2314-7307
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. (Uppsala Architecture Research Team)
2016 (English)Conference paper, Published paper (Other academic)
Abstract [en]

Understanding performance of large scale multicore systems is crucial for getting faster execution times and optimize workload efficiency, but it is becoming harder due to the increased complexity of hardware architectures. Cache sharing is a key component for performance in modern architectures, and it has been the focus of performance analysis tools and techniques in recent years.At the same time, new programming models have been introduced to aid the programmer dealing with the complexity of large scale systems, simplifying the coding process and making applications more scalable regardless of resource sharing. Task-based runtime systems are one example of this that became popular recently.In this work we develop models to tackle performance analysis of shared resources in the task-based context, and for that we study cache sharing both in temporal and spatial ways. In temporal cache sharing, the effect of data reused over time by the tasks executed is modeled to predict different scenarios resulting in a tool called StatTask. In spatial cache sharing, the effect of tasks fighting for the cache at a given point in time through their execution is quantified and used to model their behavior on arbitrary cache sizes.Finally, we explain how these tools set up a unique and solid platform to improve runtime systems schedulers, maximizing performance of execution of large-scale task-based applications.

Place, publisher, year, edition, pages
Timisoara, Romania, 2016.
Keyword [en]
task-based, cache sharing, performance analysis
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:uu:diva-284371OAI: oai:DiVA.org:uu-284371DiVA: diva2:920232
Conference
NESUS PhD Symposium on Sustainable Ultrascale Computing Systems
Projects
UPMARCNESUS
Available from: 2016-04-18 Created: 2016-04-18 Last updated: 2016-06-30Bibliographically approved

Open Access in DiVA

fulltext(249 kB)130 downloads
File information
File name FULLTEXT01.pdfFile size 249 kBChecksum SHA-512
294416bc060ef5d4f570d48f3d3d2d6e4ef0c26c02f9f6cd833d671a840ec002a34f192d06053c46b420e682819dd13f9d62aba39385fc0b9a9c76f6a4985472
Type fulltextMimetype application/pdf

Other links

Proceedings

Authority records BETA

Ceballos, GermánBlack-Schaffer, David

Search in DiVA

By author/editor
Ceballos, GermánBlack-Schaffer, David
By organisation
Computer Architecture and Computer Communication
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 130 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 279 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