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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

Compiling and Linking Your Program

Source Code Information

Static Linking

Shared Object Handling

Optimization at Compile Time

Compiling Java Programs

Preparing Your Program for Data Collection and Analysis

Using Dynamically Allocated Memory

Using System Libraries

Using Signal Handlers

Using setuid and setgid

Program Control of Data Collection

The C and C++ Interface

The Fortran Interface

The Java Interface

The C, C++, Fortran, and Java API Functions

Dynamic Functions and Modules



Limitations on Data Collection

Limitations on Clock-Based Profiling

Runtime Distortion and Dilation with Clock-profiling

Limitations on Collection of Tracing Data

Runtime Distortion and Dilation with Tracing

Limitations on Hardware Counter Overflow Profiling

Runtime Distortion and Dilation With Hardware Counter Overflow Profiling

Limitations on Data Collection for Descendant Processes

Limitations on OpenMP Profiling

Limitations on Java Profiling

Runtime Performance Distortion and Dilation for Applications Written in the Java Programming Language

Where the Data Is Stored

Experiment Names

Moving Experiments

Estimating Storage Requirements

Collecting Data

Collecting Data Using the collect Command

Data Collection Options

-p option

-h counter_definition_1...[,counter_definition_n]

-s option

-H option

-M option

-m option

-S option

-c option

-I directory

-N library_name

-r option

Experiment Control Options

-F option

-j option

-J java_argument

-l signal

-t duration


-y signal[ ,r]

Output Options

-o experiment_name

-d directory-name

-g group-name

-A option

-L size

-O file

Other Options

-P process_id

-C comment





Collecting Data From a Running Process Using the collect Utility

To Collect Data From a Running Process Using the collect Utility

Collecting Data Using the dbx collector Subcommands

To Run the Collector From dbx:

Data Collection Subcommands

profile option

hwprofile option

synctrace option

heaptrace option

tha option

sample option

dbxsample { on | off }

Experiment Control Subcommands





sample record name

Output Subcommands

archive mode

limit value

store option

Information Subcommands



Collecting Data From a Running Process With dbx on Solaris Platforms

To Collect Data From a Running Process That is Not Under the Control of dbx

Collecting Tracing Data From a Running Program

Collecting Data From MPI Programs

Running the collect Command for MPI

Storing MPI Experiments

Collecting Data From Scripts

Using collect With ppgsz

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


Collecting Data From Scripts

By default, collect requires its target to be an ELF executable and checks the target to verify this. However, you can disable this check and enable collect to run on a script that you specify as the target.

Note - Script profiling is considered an experimental feature. The implementation may change in a subsequent release.

To profile a script, you first set the environment variable SP_COLLECTOR_SKIP_CHECKEXEC to disable the checking for an ELF executable.

By default, data is collected on the program that is launched to execute the script and on all descendant processes. To collect data only on a specific process, use the -F flag to specify the name of the executable to follow. For example, to profile the script, but collect data primarily from the executable bar, use the following commands.

For csh:

% collect -F =bar

For sh:

$ collect -F =bar

Data is collected on the founder process that is launched to execute the script, and on all bar processes that are spawned from the script, but not collected for other processes.