OPAL (Object Oriented Parallel Accelerator Library) is a parallel open source tool for charged-particle optics in linear accelerators and rings, including 3D space charge. Using the MAD language with extensions, OPAL can run on a laptop as well as on the largest high performance computing systems. OPAL is built from the ground up as a parallel application exemplifying the fact that high performance computing is the third leg of science, complementing theory and experiment.

The OPAL framework makes it easy to add new features in the form of new C++ classes. OPAL comes in the following flavours:

• OPAL-cycl: tracks particles with 3D space charge including neighbouring turns in cyclotrons and FFAs with time as the independent variable.

• OPAL-t: models beam lines, linacs, rf-photo injectors and complete XFELs.

• OPAL-map: map tracking (experimental).

The code is managed through the Git distributed version control system. A suite of unit tests have been developed for various parts of OPAL, validating each part of the code independently. Unit tests use the google testing framework. System tests validate the overall integration of different elements. Documentation is written in Asciidoc. Tools are available to readily convert Asciidoc into formats such as PDF and HTML for display.

Please use the OPAL mailing list opal AT lists.psi.ch to discuss problems and issues. Subscribe to the mailing list.

Please report bugs and feature requests to the issue tracker or to the mailing list.

Git repository

git clone https://gitlab.psi.ch/OPAL/src.git

git clone --single-branch --depth 1  --branch BRANCH_OR_TAG https://gitlab.psi.ch/OPAL/src.git [DIR]

OPAL binary packages

Start with Examples

Presentations & Papers

• Using OPAL at PSI

• Supported OS and required Software to build OPAL

• Setup build environment at PSI

• Compile required software (OPAL build recipes)

• Compile OPAL

• Compile OPAL at CSCS

• The runOPAL Python scripts allows you to run, automated, several OPAL jobs and obtain the data in a conceived way. Scans of multiple dimensions are easy to perform.

• The pyOPALTools Python package contains many tools for pre- and postprocessing, and analysing and plotting output data. See also Post Processing.

• OPAL conversion utilities

Development

• Coding Style and Conventions

• Building, executing and writing unit tests

• Development workflow, Git and Gitlab usage

• Release Procedure

Documentation

• OPAL source code documentation

• IPPL Documentation

• Most Used Directories in the Code

• Technology & Ideas

• Workshops and virtual meetings

Build-, Unit- and Regression Tests

• on OPAL development branch

• on OPAL 2022.1 branch

• on OPAL 2021.1 branch

• on OPAL 2.4 branch