Input-sensitive profiling is a recent methodology for analyzing how the performance of a routine scales as a function of the workload size. As increasingly more detailed profiles are collected by an input-sensitive profiler, the information conveyed to a user can quickly become overwhelming. In this paper, we present an interactive graphical tool called aprof-plot for visualizing performance profiles. Exploiting curve fitting techniques, aprof-plot can estimate the asymptotic complexity of each routine, pointing the attention of the programmer to the most critical routines of an application. A variety of routine-based charts can be automatically generated by our tool, allowing the developer to analyze the performance scalability of a routine. Several examples based on real-world applications are discussed, showing how to conduct an effective performance investigation using aprof-plot.
An interactive visualization framework for performance analysis / Coppa, Emilio. - STAMPA. - (2014), pp. 159-164. (Intervento presentato al convegno 8th International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2014 tenutosi a Bratislava, Slovakia nel 9 December 2014 through 11 December 2014.) [10.4108/icst.valuetools.2014.258172].
An interactive visualization framework for performance analysis
COPPA, EMILIO
2014
Abstract
Input-sensitive profiling is a recent methodology for analyzing how the performance of a routine scales as a function of the workload size. As increasingly more detailed profiles are collected by an input-sensitive profiler, the information conveyed to a user can quickly become overwhelming. In this paper, we present an interactive graphical tool called aprof-plot for visualizing performance profiles. Exploiting curve fitting techniques, aprof-plot can estimate the asymptotic complexity of each routine, pointing the attention of the programmer to the most critical routines of an application. A variety of routine-based charts can be automatically generated by our tool, allowing the developer to analyze the performance scalability of a routine. Several examples based on real-world applications are discussed, showing how to conduct an effective performance investigation using aprof-plot.File | Dimensione | Formato | |
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