Insightful Performance Analysis of Many-Task Runtimes through Tool-Runtime Integration

Simple item page
dc.contributor.advisorMalony, Allen
dc.contributor.authorChaimov, Nicholas
dc.date.accessioned2017-09-06T21:53:11Z
dc.date.available2017-09-06T21:53:11Z
dc.date.issued2017-09-06
dc.description.abstractFuture supercomputers will require application developers to expose much more parallelism than current applications expose. In order to assist application developers in structuring their applications such that this is possible, new programming models and libraries are emerging, the many-task runtimes, to allow for the expression of orders of magnitude more parallelism than currently existing models. This dissertation describes the challenges that these emerging many-task runtimes will place on performance analysis, and proposes deep integration between runtimes and performance tools as a means of producing correct, insightful, and actionable performance results. I show how tool-runtime integration can be used to aid programmer understanding of performance characteristics and to provide online performance feedback to the runtime for Unified Parallel C (UPC), High Performance ParalleX (HPX), Apache Spark, the Open Community Runtime, and the OpenMP runtime.en_US
dc.identifier.urihttps://hdl.handle.net/1794/22731
dc.language.isoen_US
dc.publisherUniversity of Oregon
dc.rightsAll Rights Reserved.
dc.subjectApache Sparken_US
dc.subjectHigh performance computingen_US
dc.subjectHigh performance ParalleXen_US
dc.subjectOpen community runtimeen_US
dc.subjectTask parallelismen_US
dc.subjectUnified Parallel Cen_US
dc.titleInsightful Performance Analysis of Many-Task Runtimes through Tool-Runtime Integration
dc.typeElectronic Thesis or Dissertation
thesis.degree.disciplineDepartment of Computer and Information Science
thesis.degree.grantorUniversity of Oregon
thesis.degree.leveldoctoral
thesis.degree.namePh.D.

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Chaimov_oregon_0171A_11938.pdf
Size:
13.24 MB
Format:
Adobe Portable Document Format
Download

Collections

Theses and Dissertations
Computer Science Theses and Dissertations