extrap 4.0.0

Extra-P, automated empirical performance modeling for HPC and scientific applications

Extra-P

Automated performance modeling for HPC applications

Extra-P is an automatic performance-modeling tool that supports the user in the identification of scalability bugs. A scalability bug is a part of the program whose scaling behavior is unintentionally poor, that is, much worse than expected. A performance model is a formula that expresses a performance metric of interest such as execution time or energy consumption as a function of one or more execution parameters such as the size of the input problem or the number of processors.

Extra-P uses measurements of various performance metrics at different execution configurations as input to generate performance models of code regions (including their calling context) as a function of the execution parameters. All it takes to search for scalability issues even in full-blown codes is to run a manageable number of small-scale performance experiments, launch Extra-P, and compare the asymptotic or extrapolated performance of the worst instances to the expectations.

Extra-P generates not only a list of potential scalability bugs but also human-readable models for all performance metrics available such as floating-point operations or bytes sent by MPI calls that can be further analyzed and compared to identify the root causes of scalability issues.

Extra-P is developed by TU Darmstadt – in collaboration with ETH Zurich.

For questions regarding Extra-P please send a message to [e-mail].

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Table of Contents

1. Requirements
2. Installation
3. How to use it
4. License

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Requirements

• Python 3.7 or higher
• numpy
• pycubexr
• marshmallow
• tqdm
• PySide2 (for GUI)
• matplotlib (for GUI)
• pyobjc-framework-Cocoa (only for GUI on macOS)

Installation

Use the following command to install Extra-P and all required packages via pip.

python -m pip install extrap --upgrade

The --upgrade forces the installation of a new version if a previous version is already installed.

Usage

Extra-P can be used in two ways, either using the command-line interface or the graphical user interface. More information about the usage of Extra-P with both interfaces can be found in the quick start guide.

Graphical user interface

The graphical user interface can be started by executing the extrap-gui command.

Command line interface

The command line interface is available under the extrap command:

extrap OPTIONS (--cube | --text | --talpas | --json | --extra-p-3) FILEPATH

You can use different input formats as shown in the examples below:

• Text files: extrap --text test/data/text/one_parameter_1.txt
• JSON files: extrap --json test/data/json/input_1.JSON
• Talpas files: extrap --talpas test/data/talpas/talpas_1.txt
• Create model and save it to text file at the given path: extrap --out test.txt --text test/data/text/one_parameter_1.txt

The Extra-P command line interface has the following options.

Arguments
Positional
FILEPATH	Specify a file path for Extra-P to work with
Optional
-h, --help	Show help message and exit
--version	Show program's version number and exit
--log {DEBUG, INFO, WARNING, ERROR, CRITICAL}	Set program's log level (default: WARNING)
Input options
--cube	Load data from CUBE files
--text	Load data from text files
--talpas	Load data from Talpas data format
--json	Load data from JSON or JSON Lines file
--extra-p-3	Load data from Extra-P 3 experiment
--scaling {weak, strong}	Set weak or strong scaling when loading data from CUBE files (default: weak)
Modeling options
--median	Use median values for computation instead of mean values
--modeler {Default, Basic, Refining, Multi-Parameter}	Selects the modeler for generating the performance models
--options KEY=VALUE [KEY=VALUE ...]	Options for the selected modeler
--help-modeler {Default, Basic, Refining, Multi-Parameter}	Show help for modeler options and exit
Output options
--out OUTPUT_PATH	Specify the output path for Extra-P results
--print {all, callpaths, metrics, parameters, functions}	Set which information should be displayed after modeling (default: all)
--save-experiment EXPERIMENT_PATH	Saves the experiment including all models as Extra-P experiment (if no extension is specified, “.extra-p” is appended)

License

BSD 3-Clause "New" or "Revised" License