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Modeling the interactions between tasks and the memory system
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. (UART)ORCID iD: 0000-0003-2314-7307
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Making computer systems more energy efficient while obtaining the maximum performance possible is key for future developments in engineering, medicine, entertainment, etc. However it has become a difficult task due to the increasing complexity of hardware and software, and their interactions. For example, developers have to deal with deep, multi-level cache hierarchies on modern CPUs, and keep busy thousands of cores in GPUs, which makes the programming process more difficult.

To simplify this task, new abstractions and programming models are becoming popular. Their goal is to make applications more scalable and efficient, while still providing the flexibility and portability of old, widely adopted models. One example of this is task-based programming, where simple independent tasks (functions) are delegated to a runtime system which orchestrates their execution. This approach has been successful because the runtime can automatically distribute work across hardware cores and has the potential to minimize data movement and placement (e.g., being aware of the cache hierarchy).

To build better runtime systems, it is crucial to understand bottlenecks in the performance of current and future multicore systems. In this thesis, we provide fast, accurate and mathematically-sound models and techniques to understand the execution of task-based applications concerning three key aspects: memory behavior (data locality), scheduling, and performance. With these methods, we lay the groundwork for improving runtime system, providing insight into the interplay between the schedule's behavior, data reuse through the cache hierarchy, and the resulting performance.

Place, publisher, year, edition, pages
Uppsala University, 2017.
Series
Information technology licentiate theses: Licentiate theses from the Department of Information Technology, ISSN 1404-5117 ; 2017-002
National Category
Computer Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:uu:diva-335530OAI: oai:DiVA.org:uu-335530DiVA, id: diva2:1163319
Supervisors
Projects
UPMARCAvailable from: 2017-10-01 Created: 2017-12-06 Last updated: 2018-01-31Bibliographically approved
List of papers
1. Shared Resource Sensitivity in Task-Based Runtime Systems
Open this publication in new window or tab >>Shared Resource Sensitivity in Task-Based Runtime Systems
2013 (English)In: Proc. 6th Swedish Workshop on Multi-Core Computing, Halmstad University Press, 2013Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Halmstad University Press, 2013
National Category
Computer Systems
Identifiers
urn:nbn:se:uu:diva-212780 (URN)
Conference
MCC13, November 25–26, Halmstad, Sweden
Projects
Resource Sharing ModelingUPMARC
Funder
Swedish Research Council
Available from: 2013-12-13 Created: 2013-12-13 Last updated: 2018-01-26Bibliographically approved
2. Formalizing data locality in task parallel applications
Open this publication in new window or tab >>Formalizing data locality in task parallel applications
2016 (English)In: Algorithms and Architectures for Parallel Processing, Springer, 2016, p. 43-61Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Springer, 2016
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10049
National Category
Computer Sciences
Identifiers
urn:nbn:se:uu:diva-310341 (URN)10.1007/978-3-319-49956-7_4 (DOI)000389797000004 ()978-3-319-49955-0 (ISBN)
Conference
ICA3PP 2016, December 14–16, Granada, Spain
Projects
UPMARCResource Sharing Modeling
Funder
Swedish Foundation for Strategic Research , FFL12-0051
Available from: 2016-11-19 Created: 2016-12-14 Last updated: 2018-01-26Bibliographically approved
3. TaskInsight: Understanding task schedules effects on memory and performance
Open this publication in new window or tab >>TaskInsight: Understanding task schedules effects on memory and performance
2017 (English)In: Proc. 8th International Workshop on Programming Models and Applications for Multicores and Manycores, New York: ACM Press, 2017, p. 11-20Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
New York: ACM Press, 2017
National Category
Computer Engineering
Identifiers
urn:nbn:se:uu:diva-315033 (URN)10.1145/3026937.3026943 (DOI)978-1-4503-4883-6 (ISBN)
Conference
PMAM 2017, February 4–8, Austin, TX
Projects
UPMARCResource Sharing Modeling
Funder
Swedish Research CouncilSwedish Foundation for Strategic Research , FFL12-0051EU, Horizon 2020, 687698
Available from: 2017-02-04 Created: 2017-02-08 Last updated: 2018-01-26Bibliographically approved
4. Analyzing performance variation of task schedulers with TaskInsight
Open this publication in new window or tab >>Analyzing performance variation of task schedulers with TaskInsight
2018 (English)In: Parallel Computing, ISSN 0167-8191, E-ISSN 1872-7336, Vol. 75, p. 11-27Article in journal (Refereed) Published
National Category
Computer Engineering
Identifiers
urn:nbn:se:uu:diva-340202 (URN)10.1016/j.parco.2018.02.003 (DOI)
Projects
UPMARCResource Sharing Modeling
Available from: 2018-02-22 Created: 2018-01-26 Last updated: 2018-03-03Bibliographically approved

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Ceballos, Germán

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