Critical path analysis tool for heterogeneous applications (CASITA)
Contributing person | Dietrich, Robert | |
Contributing person | Schmitt, Felix | |
Contributing person | Stolle, Jonas | |
Documentation of the data | The source code has to be compiled with a C++ compiler. Make sure to have an MPI and an OTF2 library in the library path. Build and compile with the following commands: cmake .; make Execute the binary 'casita -h' for a help output on the execution options of CASITA. | |
References to related material | https://github.com/rdietric/casita | |
References to related material | 10.1177/1094342016661865 | |
References to related material | 10.1109/ICPPW.2014.35 | |
Type of the data | Software | |
Total size of the dataset | 190156 | |
Author | Dietrich, Robert | |
Upload date | 2019-05-02T10:52:53Z | |
Publication date | 2019-05-02T10:52:53Z | |
Publication date | 2026-05-18T14:15:31Z | |
Data of data creation | 2013-2019 | |
Publication date | 2019-05-02 | |
Abstract of the dataset | CASITA is a tool for automatic analysis of OTF2 trace files that have been generated with Score-P. It determines program activities with high impact on the total program runtime and the load balancing. CASITA generates an OTF2 trace with additional information such as the critical path, waiting time, and the cause of wait states. The same metrics are used to generate a summary profile which rates activities according their potential to improve the program runtime and the load balancing. A summary of inefficient patterns exposes waiting times in the individual programming models and APIs. CASITA version 1.9 has been used as proof-of-concept implementation for the dissertation "Scalable Applications on Heterogeneous System Architectures: A Systematic Performance Analysis Framework". Compiling the source code of CASITA requires OTF2 and an MPI library such as OpenMPI. | |
Public reference to this page | https://opara.zih.tu-dresden.de/handle/123456789/2324 | |
Public reference to this page | https://doi.org/10.25532/OPARA-28 | |
Publisher | Technische Universität Dresden | |
Specification of the discipline(s) | 4::44::409 | |
Title of the dataset | Critical path analysis tool for heterogeneous applications (CASITA) | |
dc.title.alternative | Source Code | |
Project abstract | 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. As waiting or idle time can propagate over multiple levels of parallelism, e.g. from a delayed task on an accelerator over host threads to another compute node, the actual cause of an inefficiency might be difficult to find. This thesis proposes a framework for systematic performance analysis of scalable, heterogeneous applications, which covers process- and thread-level parallelism as well as computation offloading. It addresses two essential aspects that have so far been neglected: potential inefficiencies with computation offloading and generic analyses across programming models. Furthermore, established analyses are combined in such a way that inefficiencies and program regions can be prioritized to enable a more focused optimization process. The analysis results are presented in form of a program region profile, a summary of all inefficiencies, and timelines. In the core analyses, the implementation is independent of application programming interfaces (APIs) and can detect further inefficiencies and wait states by adding new analysis rules. It is applied to synthetic and real-world programs to validate the applicability, correctness, and scalability. | |
Project title | Scalable Applications on Heterogeneous System Architectures: A Systematic Performance Analysis Framework |
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