Intel® Advisor User Guide

ID 766448
Date 7/13/2023
Public

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collect.py Options

Depending on options specified, collect basic data, do markup, and collect refinement data. By default, execute all steps. For any step besides markup, you must specify an application argument.

Usage

advisor-python <APM>/collect.py <project-dir> [--options] -- <target> [target-options]

NOTE:
Replace <APM> with $APM on Linux* OS or %APM% on Windows* OS.

Options

The following table describes options that you can use with the collect.py script. The target application to analyze and application options, if any, must be preceded by two dashes and a space.

Option

Description

<project-dir>

Required. Specify the path to the Intel® Advisor project directory.

-h

--help

Show all script options.

-v <verbose>

--verbose <verbose>

Specify output verbosity level:

  • 1 - Show only error messages. This is the least verbose level.

  • 2 - Show warning and error messages.

  • 3 (default) - Show information, warning, and error messages.

  • 4 - Show debug, information, warning, and error messages. This is the most verbose level.

NOTE:
This option affects the console output, but does not affect logs and report results.

-c {basic, refinement, full}

--collect {basic, refinement, full}

Specify the type of data to collect for an application:

  • basic - Collect basic performance data (Survey, Trip Counts, FLOP), analyze data transfer between host and device memory, attribute memory objects to loops, and track accesses to stack memory.
  • refinement - Collect refined data (Dependencies) for marked loops only. Do not analyze data transfers.
  • full (default) - Collect both basic data for application and refined data for marked loops, analyze data transfer between host and device memory and potential data reuse, attribute memory objects to loops, and track accesses to stack memory.
NOTE:
For --collect full, make sure to use --data-reuse-analysis and --track-memory-objects for the Performance modeling with analyze.py or advisor --collect=projection.

For --collect basic, make sure to use the --track-memory-objects for the Performance modeling with analyze.py or advisor --collect=projection.

--config <config>

Specify a configuration file by absolute path or name. If you choose the latter, the model configuration directory is searched for the file first, then the current directory.

You can specify several configurations by using the option more than once.

--data-reuse-analysis | --no-data-reuse-analysis (default)

Estimate data reuse between offloaded regions. Disabling can decrease analysis overhead.

IMPORTANT:
--collect basic and --collect full overwrite this option. To add the data reuse analysis results to the Offload Modeling report, make sure to use the --data-reuse-analysis option for the Performance modeling with analyze.py or advisor --collect=projection.

--data-transfer (default) | --no-data-transfer

Analyze data transfer.

NOTE:
Disabling can decrease analysis overhead.

--dry-run

Show the Intel® Advisor CLI commands for advisor appropriate for the specified configuration. No actual collection is performed.

--enable-edram

Enable eDRAM modeling in the memory hierarchy model.

IMPORTANT:
Make sure to use this option with both collect.py and analyze.py.

--enable-slm

Enable SLM modeling in the memory hierarchy model.

IMPORTANT:
Make sure to use this option with both collect.py and analyze.py.

--executable-of-interest <executable-name>

Specify the executable process name to profile if it is not the same as the application to run. Use this option if you run your application via script or other binary.

NOTE:
Specify the name only, not the full path.

--flex-cachesim <cache-configuration>

Use flexible cache simulation to model cache data for several target devices. The flexible cache simulation allows you to change a device for an analysis without recollecting data. By default, when no configuration is set, cache data is simulated for all supported target platforms.

You can also specify a list of cache configurations separated with a forward slash in the format <size_of_level1>:<size_of_level2>:<size_of_level3>. For each memory level size, specify a unit of measure as b - bytes, k- kilobytes, or m - megabytes.

For example, 8k:512k:8m/24k:1m:8m/32k:1536k:8m.

--gpu (recommended) | --profile-gpu | --analyze-gpu-kernels-only

Model performance only for code regions running on a GPU. Use one of the three options.

IMPORTANT:
Make sure to specify this option for both collect.py and analyze.py.
NOTE:
This is a preview feature. --analyze-gpu-kernels-only is deprecated and will be removed in futire releases.

--no-profile-jit (default)

Disable JIT function analysis.