Sun Studio 12 Update 1: Performance Analyzer

The Tools of Performance Analysis

This manual describes the Collector and Performance Analyzer, a pair of Sun Studio tools that you use to collect and analyze performance data for your application. Both tools can be used from the command line or from a graphical user interface.

The Collector and Performance Analyzer are designed for use by any software developer, even if performance tuning is not the developer’s main responsibility. These tools provide a more flexible, detailed, and accurate analysis than the commonly used profiling tools prof and gprof, and are not subject to an attribution error in gprof.

The Collector and Performance Analyzer tools help to answer the following kinds of questions:

The Collector Tool

The Collector tool collects performance data using a statistical method called profiling and by tracing function calls. The data can include call stacks, microstate accounting information (on Solaris platforms only), thread synchronization delay data, hardware counter overflow data, Message Passing Interface (MPI) function call data, memory allocation data, and summary information for the operating system and the process. The Collector can collect all kinds of data for C, C++ and Fortran programs, and it can collect profiling data for applications written in the JavaTM programming language. It can collect data for dynamically-generated functions and for descendant processes. See Chapter 2, Performance Data for information about the data collected and Chapter 3, Collecting Performance Data for detailed information about the Collector. The Collector can be run from the Performance Analyzer GUI, from the IDE, from the dbx command line tool, and using the collect command.

The Performance Analyzer Tool

The Performance Analyzer tool displays the data recorded by the Collector, so that you can examine the information. The Performance Analyzer processes the data and displays various metrics of performance at the level of the program, the functions, the source lines, and the instructions. These metrics are classed into five groups:

The Performance Analyzer also displays the raw data in a graphical format as a function of time. The Performance Analyzer can create a mapfile that you can use to change the order of function loading in the program’s address space, to improve performance.

See Chapter 4, The Performance Analyzer Tool and the online help in the IDE or the Performance Analyzer GUI for detailed information about the Performance Analyzer.

Chapter 5, Kernel Profiling describes how you can use the Sun Studio performance tools to profile the kernel while the SolarisTM Operating System (Solaris OS) is running a load.

Chapter 6, The er_print Command Line Performance Analysis Tool describes how to use the er_print command line interface to analyze the data collected by the Collector.

Chapter 7, Understanding the Performance Analyzer and Its Data discusses topics related to understanding the performance analyzer and its data, including: how data collection works, interpreting performance metrics, call stacks and program execution, and annotated code listings. Annotated source code listings and disassembly code listings that include compiler commentary but do not include performance data can be viewed with the er_src utility (see Chapter 8, Understanding Annotated Source and Disassembly Data for more information).

Chapter 8, Understanding Annotated Source and Disassembly Data provides an understanding of the annotated source and disassembly, providing explanations about the different types of index lines and compiler commentary that the Performance Analyzer displays.

Chapter 9, Manipulating Experiments describes how to copy, move, delete, archive, and export experiments.

The er_print Utility

The er_print utility presents in plain text all the displays that are presented by the Performance Analyzer, with the exception of the Timeline display, the MPI Timeline display, and the MPI Chart display.