The Parla runtime

dc.contributor.advisorErez, Mattan
dc.contributor.committeeMemberRossbach, Christopher J
dc.creatorStephens, Sean Edward
dc.date.accessioned2022-12-14T02:14:59Z
dc.date.available2022-12-14T02:14:59Z
dc.date.created2022-05
dc.date.issued2022-05-05
dc.date.submittedMay 2022
dc.date.updated2022-12-14T02:15:00Z
dc.description.abstractWriting high-performance programs to target heterogeneous compute nodes poses many challenges associated with properly managing data-level and task-level parallelism across various processing units. Parla is a heterogeneous task-based programming framework which simplifies writing portable multi-device code by enabling programmers to leverage task-level parallelism with simple decorator annotations while fully utilizing Python’s rich scientific programming stack. The underlying runtime system of Parla must support the efficient execution of a variety of task graphs on complex heterogeneous nodes. This runtime is divided into three phases: mapper, scheduler, and launcher. I present the design of each phase and discuss the motivation behind design decisions, with particular attention to the performant treatment of GPU tasks. I show that the current runtime’s heuristic-based mapping policies run similarly well to optimal user-specified mappings on a variety of workloads. Lastly, I detail many areas of future work to further improve the runtime performance.
dc.description.departmentElectrical and Computer Engineering
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2152/116979
dc.identifier.urihttp://dx.doi.org/10.26153/tsw/43874
dc.language.isoen
dc.subjectParallel application frameworks
dc.subjectTask-based parallelism
dc.subjectHeterogeneous computing
dc.subjectLoad balancing and scheduling algorithms
dc.titleThe Parla runtime
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelMasters
thesis.degree.nameMaster of Science in Engineering

Access full-text files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
STEPHENS-MASTERSREPORT-2022.pdf
Size:
604.64 KB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 2 of 2
No Thumbnail Available
Name:
PROQUEST_LICENSE.txt
Size:
4.45 KB
Format:
Plain Text
Description:
No Thumbnail Available
Name:
LICENSE.txt
Size:
1.84 KB
Format:
Plain Text
Description: