- AutorIn
- Robert Dietrich
- Titel
- Scalable Applications on Heterogeneous System Architectures
- Untertitel
- A Systematic Performance Analysis Framework
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-361678
- Übersetzter Titel (DE)
- Skalierbare Anwendungen auf heterogenen Systemarchitekturen: Ein systematisches Leistungsanalyse-Framework
- Datum der Einreichung
- 06.05.2019
- Datum der Verteidigung
- 09.10.2019
- Abstract (EN)
- The efficient parallel execution of scientific applications is a key challenge in high-performance computing (HPC). With growing parallelism and heterogeneity of compute resources as well as increasingly complex software, performance analysis has become an indispensable tool in the development and optimization of parallel programs. This thesis presents a framework for systematic performance analysis of scalable, heterogeneous applications. Based on event traces, it automatically detects the critical path and inefficiencies that result in waiting or idle time, e.g. due to load imbalances between parallel execution streams. As a prerequisite for the analysis of heterogeneous programs, this thesis specifies inefficiency patterns for computation offloading. Furthermore, an essential contribution was made to the development of tool interfaces for OpenACC and OpenMP, which enable a portable data acquisition and a subsequent analysis for programs with offload directives. At present, these interfaces are already part of the latest OpenACC and OpenMP API specification. The aforementioned work, existing preliminary work, and established analysis methods are combined into a generic analysis process, which can be applied across programming models. Based on the detection of wait or idle states, which can propagate over several levels of parallelism, the analysis identifies wasted computing resources and their root cause as well as the critical-path share for each program region. Thus, it determines the influence of program regions on the load balancing between execution streams and the program runtime. The analysis results include a summary of the detected inefficiency patterns and a program trace, enhanced with information about wait states, their cause, and the critical path. In addition, a ranking, based on the amount of waiting time a program region caused on the critical path, highlights program regions that are relevant for program optimization. The scalability of the proposed performance analysis and its implementation is demonstrated using High-Performance Linpack (HPL), while the analysis results are validated with synthetic programs. A scientific application that uses MPI, OpenMP, and CUDA simultaneously is investigated in order to show the applicability of the analysis.
- Verweis
- Analyzing Offloading Inefficiencies in Scalable Heterogeneous Applications
DOI: 10.1007/978-3-319-67630-2_34 - CASITA: A Tool for Identifying Critical Optimization Targets in Distributed Heterogeneous Applications
DOI: 10.1109/ICPPW.2014.35 - Characterizing Load and Communication Imbalance in Parallel Applications
PhD thesis by David Böhme
Link: https://publications.rwth-aachen.de/record/229075/files/4986.pdf - Scalable critical-path analysis and optimization guidance for hybrid MPI-CUDA applications
DOI: 10.1177/1094342016661865 - OpenACC Programs Examined: A Performance Analysis Approach
DOI: 10.1109/ICPP.2015.40 - Forschungsdatenverweis
- Critical path analysis tool for heterogeneous applications (CASITA)
DOI: 10.25532/OPARA-28 - Freie Schlagwörter (DE)
- Leistungsanalyse, kritischer Pfad, heterogene Systeme, Wartezustände
- Freie Schlagwörter (EN)
- performance analysis, heterogeneous systems, critical path, root cause
- Klassifikation (DDC)
- 004
- Klassifikation (RVK)
- ST 151
- GutachterIn
- Prof. Dr. rer. nat. Wolfgang E. Nagel
- Prof. Dr. rer. nat. Matthias Müller
- Den akademischen Grad verleihende / prüfende Institution
- Technische Universität Dresden, Dresden
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-361678
- Veröffentlichungsdatum Qucosa
- 15.11.2019
- Dokumenttyp
- Dissertation
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis