Extending the Functionality of Score-P Through Plugins: Interfaces and Use Cases

Robert Schöne (), Ronny Tschüter (), Thomas Ilsche (), Joseph Schuchart (), Daniel Hackenberg () and Wolfgang E. Nagel ()
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Robert Schöne: Technische Universität Dresden, Center for Information Services and High Performance Computing (ZIH)
Ronny Tschüter: Technische Universität Dresden, Center for Information Services and High Performance Computing (ZIH)
Thomas Ilsche: Technische Universität Dresden, Center for Information Services and High Performance Computing (ZIH)
Joseph Schuchart: University of Stuttgart, High Performance Computing Center Stuttgart (HLRS)
Daniel Hackenberg: Technische Universität Dresden, Center for Information Services and High Performance Computing (ZIH)
Wolfgang E. Nagel: Technische Universität Dresden, Center for Information Services and High Performance Computing (ZIH)

A chapter in Tools for High Performance Computing 2016, 2017, pp 59-82 from Springer

Abstract: Abstract Performance measurement and runtime tuning tools are both vital in the HPC software ecosystem and use similar techniques: the analyzed application is interrupted at specific events and information on the current system state is gathered to be either recorded or used for tuning. One of the established performance measurement tools is Score-P. It supports numerous HPC platforms and parallel programming paradigms. To extend Score-P with support for different back-ends, create a common framework for measurement and tuning of HPC applications, and to enable the re-use of common software components such as implemented instrumentation techniques, this paper makes the following contributions: (1) We describe the Score-P metric plugin interface, which enables programmers to augment the event stream with metric data from supplementary data sources that are otherwise not accessible for Score-P. (2) We introduce the flexible Score-P substrate plugin interface that can be used for custom processing of the event stream according to the specific requirements of either measurement, analysis, or runtime tuning tasks. (3) We provide examples for both interfaces that extend Score-P’s functionality for monitoring and tuning purposes.

Keywords: High Performance Computing; Runtime Overhead; Spatial Scope; OpenMP Thread; Hardware Thread (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/978-3-319-56702-0_4

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