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SPLASH 2017
Sun 22 - Fri 27 October 2017 Vancouver, Canada

Performance measurement and analysis are commonly carried out tasks for high-performance computing applications. Both sampling and instrumentation approaches for performance measurement can capture hardware performance counter (HWPC) metrics to asses the software’s ability to use the functional units of the processor. Since the measurement software usually executes on the same processor, it necessarily competes with the target application for hardware resources. Consequently, the measurement system perturbs the target application, which often results in runtime overhead. While the runtime overhead of different measurement techniques has been previously studied, it has not been thoroughly examined to what extent HWPC values are perturbed by the measurement process. In this paper, we investigate the influence of the two widely-used performance measurement systems HPCToolkit (sampling) and Score-P (instrumentation) w.r.t. their influence on HWPC. Our experiments on the SPEC CPU 2006 C/C++ benchmarks show that, while Score-P’s default instrumentation can massively increase runtime, it does not always heavily perturb relevant HWPC. On the other hand, HPCToolkit shows no significant runtime overhead, but significantly influences some relevant HWPC. We conclude that for every performance experiment sufficient baseline measurements are essential to identify the HWPC that remain valid indicators of performance for a given measurement technique. Thus, performance analysis tools need to offer easily accessible means to automate the baseline and validation functionality.

Mon 23 Oct

Displayed time zone: Tijuana, Baja California change

10:30 - 12:00
Session2: Software performance engineeringSEPS at Brighton
Chair(s): Pablo de Oliveira Castro University of Versailles, France
10:30
30m
Talk
MALT, A Malloc Tracker
SEPS
Sébastien Valat CERN, Andres S. Charif-Rubial Université de Versailles Saint-Quentin, William Jalby Université de Versalles
11:00
30m
Talk
Performance Analysis and Optimization of the RAMPAGE Metal Alloy Potential Generation Software
SEPS
Philip C. Roth Oak Ridge National Laboratory, Hongzhang Shan Lawrence Berkeley National Laboratory, David Riegner The Ohio State University, Nikolas Antolin The Ohio State University, Sarat Sreepathi Oak Ridge National Laboratory, Leonid Oliker Lawrence Berkeley National Laboratory, Samuel Williams Lawrence Berkeley National Laboratory, Shirley Moore Oak Ridge National Laboratory, Wolfgang Windl The Ohio State University
11:30
30m
Talk
The Influence of HPCToolkit and Score-P on Hardware Performance Counters
SEPS
Jan-Patrick Lehr Graduate School of Computational Engineering, TU Darmstadt, Christian Iwainsky Competence Center for High-Performance Computing in Hessian, TU Darmstadt, Christian Bischof Scientific Computing, TU Darmstadt