Enabling Data Structure Oriented Performance Analysis with Hardware Performance Counter Support

Authors:
Karl Fürlinger;Dan Terpstra;Haihang You;Phil Mucci;Shirley Moore
Affiliations:
Computer Science Division, EECS Department, University of California at Berkeley, and Innovative Computing Laboratory, Department of Electrical Engineering and Computer Science, University of Tenn ...;Innovative Computing Laboratory, Department of Electrical Engineering and Computer Science, University of Tennessee,;Innovative Computing Laboratory, Department of Electrical Engineering and Computer Science, University of Tennessee,;Innovative Computing Laboratory, Department of Electrical Engineering and Computer Science, University of Tennessee,;Innovative Computing Laboratory, Department of Electrical Engineering and Computer Science, University of Tennessee,
Venue:
Euro-Par 2008 Workshops - Parallel Processing
Year:
2009

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Abstract

An interesting and as of yet under-represented aspect of program development and optimization are data structures. Instead of analyzing data with respect to code regions, the objective here is to see how performance metrics are related to data structures. With the advanced performance monitoring unit of Intel's Itanium processor series such an analysis becomes possible. This paper describes how the hardware features of the Itanium 2 processor are exploited by the perfmon and PAPI performance monitoring APIs and how PAPI's support for address range restrictions has been integrated into an existing profiling tool to achieve the goal of data structure oriented profiling in the context of OpenMP applications.