Hofmann F, Bolch G (1994)
Publication Type: Other publication type
Publication year: 1994
Publisher: Elsevier
Book Volume: 20
Pages Range: 21
Journal Issue: TR-I4-94-24
DOI: 10.1016/0167-8191(94)90058-2
Modeling parallel programs can help the developer during the design phase of a particular implementation on the one hand and on the other hand provide principle insights which are needed to establish design principles for the development of parallel programs. It is important that the model used provides a sufficient but not too detailed representation of the parallel program. Precedence graphs provide an easy to understand representation of the structure of parallel programs. Information about the behavior of parallel programs during execution can be obtained by assigning distributions of the execution times of the subtasks to the nodes of these graphs. In this paper we introduce truncated θ-exponential polynomials as a class of distributions suitable for the modeling of task run-times of massively parallel programs. As opposed to classical exponential polynomials known from literature, truncated θ-exponential polynomials allow the representation of distributions with finite domain and are therefore appropriate for the analysis of massively parallel systems. We present approximation formulas which allow the approximate calculation of the total execution time for large models in particular. We provide formulas for the parallel execution of a large number of subtasks. We also give a method to estimate the total execution time of regular graphs, which are also very important in the field of modeling parallel programs. © 1994.
APA:
Hofmann, F., & Bolch, G. (1994). Performance analysis of parallel programs based on model calculations. Elsevier.
MLA:
Hofmann, Fridolin, and Gunter Bolch. Performance analysis of parallel programs based on model calculations. Elsevier, 1994.
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