Performance analysis techniques for task-based OpenMP applications

Authors:
Dirk Schmidl;Peter Philippen;Daniel Lorenz;Christian Rössel;Markus Geimer;Dieter an Mey;Bernd Mohr;Felix Wolf
Affiliations:
RWTH Aachen University, Aachen, Germany;Jülich Supercomputing Centre, Jülich, Germany;Jülich Supercomputing Centre, Jülich, Germany;Jülich Supercomputing Centre, Jülich, Germany;Jülich Supercomputing Centre, Jülich, Germany;RWTH Aachen University, Aachen, Germany;Jülich Supercomputing Centre, Jülich, Germany;RWTH Aachen University, Aachen, Germany,Jülich Supercomputing Centre, Jülich, Germany,German Research School for Simulation Sciences, Aachen, Germany
Venue:
IWOMP'12 Proceedings of the 8th international conference on OpenMP in a Heterogeneous World
Year:
2012

Citing 8
Cited 0

Design and Prototype of a Performance Tool Interface for OpenMP

The Journal of Supercomputing
The Tau Parallel Performance System

International Journal of High Performance Computing Applications
Providing Observability for OpenMP 3.0 Applications

IWOMP '09 Proceedings of the 5th International Workshop on OpenMP: Evolving OpenMP in an Age of Extreme Parallelism
Performance Profiling for OpenMP Tasks

IWOMP '09 Proceedings of the 5th International Workshop on OpenMP: Evolving OpenMP in an Age of Extreme Parallelism
Barcelona OpenMP Tasks Suite: A Set of Benchmarks Targeting the Exploitation of Task Parallelism in OpenMP

ICPP '09 Proceedings of the 2009 International Conference on Parallel Processing
HPCTOOLKIT: tools for performance analysis of optimized parallel programs http://hpctoolkit.org

Concurrency and Computation: Practice & Experience - Scalable Tools for High-End Computing
The Scalasca performance toolset architecture

Concurrency and Computation: Practice & Experience - Scalable Tools for High-End Computing
How to reconcile event-based performance analysis with tasking in OpenMP

IWOMP'10 Proceedings of the 6th international conference on Beyond Loop Level Parallelism in OpenMP: accelerators, Tasking and more

Quantified Score

Hi-index	0.00

Visualization

Abstract

Version 3.0 of the OpenMP specification introduced the task construct for the explicit expression of dynamic task parallelism. Although automated load-balancing capabilities make it an attractive parallelization approach for programmers, the difficulty of integrating this new dimension of parallelism into traditional models of performance data has so far prevented the emergence of appropriate performance tools. Based on our earlier work, where we have introduced instrumentation for task-based programs, we present initial concepts for analyzing the data delivered by this instrumentation. We define three typical performance problems related to tasking and show how they can be visually explored using event traces. Special emphasis is placed on the event model used to capture the execution of task instances and on how the time consumed by the program is mapped onto tasks in the most meaningful way. We illustrate our approach with practical examples.