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Oracle Solaris Studio 12.2: Performance Analyzer
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Document Information


1.  Overview of the Performance Analyzer

2.  Performance Data

What Data the Collector Collects

Clock Data

Clock-based Profiling Under the Solaris OS

Clock-based Profiling Under the Linux OS

Clock-based Profiling for MPI Programs

Clock-based Profiling for OpenMP Programs

Hardware Counter Overflow Profiling Data

Hardware Counter Lists

Format of the Aliased Hardware Counter List

Format of the Raw Hardware Counter List

Synchronization Wait Tracing Data

Heap Tracing (Memory Allocation) Data

MPI Tracing Data

Global (Sampling) Data

How Metrics Are Assigned to Program Structure

Function-Level Metrics: Exclusive, Inclusive, and Attributed

Interpreting Attributed Metrics: An Example

How Recursion Affects Function-Level Metrics

3.  Collecting Performance Data

4.  The Performance Analyzer Tool

5.  The er_print Command Line Performance Analysis Tool

6.  Understanding the Performance Analyzer and Its Data

7.  Understanding Annotated Source and Disassembly Data

8.  Manipulating Experiments

9.  Kernel Profiling


Chapter 2

Performance Data

The performance tools work by recording data about specific events while a program is running, and converting the data into measurements of program performance called metrics. Metrics can be shown against functions, source lines, and instructions.

This chapter describes the data collected by the performance tools, how it is processed and displayed, and how it can be used for performance analysis. Because there is more than one tool that collects performance data, the term Collector is used to refer to any of these tools. Likewise, because there is more than one tool that analyzes performance data, the term analysis tools is used to refer to any of these tools.

This chapter covers the following topics.

See Chapter 3, Collecting Performance Data for information on collecting and storing performance data.