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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

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

How Data Collection Works

Experiment Format

The archives Directory

Descendant Processes

Dynamic Functions

Java Experiments

Recording Experiments

collect Experiments

dbx Experiments That Create a Process

dbx Experiments on a Running Process

Interpreting Performance Metrics

Clock-Based Profiling

Accuracy of Timing Metrics

Comparisons of Timing Metrics

Synchronization Wait Tracing

Hardware Counter Overflow Profiling

Heap Tracing

Dataspace Profiling

MPI Tracing

Call Stacks and Program Execution

Single-Threaded Execution and Function Calls

Function Calls Between Shared Objects



Tail-Call Optimization

Explicit Multithreading

Overview of Java Technology-Based Software Execution

Java Call Stacks and Machine Call Stacks

Clock-based Profiling and Hardware Counter Overflow Profiling

Java Processing Representations

The User Representation

The Expert-User Representation

The Machine Representation

Overview of OpenMP Software Execution

User Mode View of OpenMP Profile Data

Artificial Functions

User Mode Call Stacks

OpenMP Metrics

Expert View Mode of OpenMP Profiling Data

Machine View Mode of OpenMP Profiling Data

Incomplete Stack Unwinds

Intermediate Files

Mapping Addresses to Program Structure

The Process Image

Load Objects and Functions

Aliased Functions

Non-Unique Function Names

Static Functions From Stripped Shared Libraries

Fortran Alternate Entry Points

Cloned Functions

Inlined Functions

Compiler-Generated Body Functions

Outline Functions

Dynamically Compiled Functions

The <Unknown> Function

OpenMP Special Functions

The <JVM-System> Function

The <no Java callstack recorded> Function

The <Truncated-stack> Function

The <Total> Function

Functions Related to Hardware Counter Overflow Profiling

Mapping Performance Data to Index Objects

Mapping Data Addresses to Program Data Objects

Data Object Descriptors

The <Total> Data Object

The <Scalars> Data Object

The <Unknown> Data Object and Its Elements

Mapping Performance Data to Memory Objects

7.  Understanding Annotated Source and Disassembly Data

8.  Manipulating Experiments

9.  Kernel Profiling


Chapter 6

Understanding the Performance Analyzer and Its Data

The Performance Analyzer reads the event data that is collected by the Collector and converts it into performance metrics. The metrics are computed for various elements in the structure of the target program, such as instructions, source lines, functions, and load objects. In addition to a header containing a timestamp, thread id, LWP id, and CPU id, the data recorded for each event collected has two parts:

The process of associating the metrics with the program structure is not always straightforward, due to the insertions, transformations, and optimizations made by the compiler. This chapter describes the process and discusses the effect on what you see in the Performance Analyzer displays.

This chapter covers the following topics: