Ginkgo: Contributing guidelines

| Ginkgo Generated from branch based on main. Ginkgo version 1.11.0 A numerical linear algebra library targeting many-core architectures

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Contributing guidelines

We are glad that you are interested in contributing to Ginkgo. Please have a look at our coding guidelines before proposing a pull request.

# Table of Contents

Most Important stuff

Project Structure

- Extended header files
- Using library classes

Git related

- Our git Workflow
- Writing good commit messages
- Creating, Reviewing and Merging Pull Requests

Code Style

- Automatic code formatting
- Naming Scheme
- Whitespace
- Include statement grouping
- Other Code Formatting not handled by ClangFormat
- CMake coding style

Helper Scripts

- Create a new algorithm
- Converting CUDA code to HIP code

Writing Tests

- Testing know-how
- Some general rules
- Writing tests for kernels

Documentation style

- Developer targeted notes
- Whitespaces
- Documenting examples

Other programming comments

- C++ standard stream objects
- Warnings
- Avoiding circular dependencies

# Most important stuff (A TL;DR)

- GINKGO_DEVEL_TOOLS needs to be set to on to commit. This requires clang-format to be installed. See Automatic code formatting for more details. Once installed, you can run make format in your build/ folder to automatically format your modified files. As make format unstages your files post-formatting, you must stage the files again once you have verified that make format has done the appropriate formatting, before committing the files.
- See Our git workflow to get a quick overview of our workflow.
- See Creating, Reviewing and Merging Pull Requests on how to create a Pull request.

# Project structure

Ginkgo is divided into a core module with common functionalities independent of the architecture, and several kernel modules (reference, omp, cuda, hip, dpcpp) which contain low-level computational routines for each supported architecture.

## Extended header files

Some header files from the core module have to be extended to include special functionality for specific architectures. An example of this is core/base/math.hpp, which has a GPU counterpart in cuda/base/math.hpp. For such files you should always include the version from the module you are working on, and this file will internally include its core counterpart.

## Using library classes

You can use and call functions of existing classes inside a kernel (that are defined and not just declared in a header file), however, you are not allowed to create new instances of a polymorphic class inside a kernel (or in general inside any kernel module like cuda/hip/omp/reference) as this creates circular dependencies between the core and the backend library. With this in mind, our CI contains a job which checks if such a circular dependency exists. These checks can be run manually using the -DGINKGO_CHECK_CIRCULAR_DEPS=ON option in the CMake configuration.

For example, when creating a new matrix class AB by combining existing classes A and B, the AB::apply() function composed of invocations to A::apply() and B::apply() can only be defined in the core module, it is not possible to create instances of A and B inside the AB kernel files. This is to avoid the aforementioned circular dependency issue. An example for such a class is the Hybrid matrix format, which uses the apply() of the Ell and Coo matrix formats. Nevertheless, it is possible to call the kernels themselves directly within the same executor. For example, cuda::dense::add_scaled() can be called from any other cuda kernel.

# Git related

Ginkgo uses git, the distributed version control system to track code changes and coordinate work among its developers. A general guide to git can be found in its extensive documentation.

## Our git workflow

In Ginkgo, we prioritize keeping a clean history over accurate tracking of commits. git rebase is hence our command of choice to make sure that we have a nice and linear history, especially for pulling the latest changes from the develop branch. More importantly, rebasing upon develop is required before the commits of the PR are merged into the develop branch.

## Writing good commit messages

With software sustainability and maintainability in mind, it is important to write commit messages that are short, clear and informative. Ideally, this would be the format to prefer:

Summary of the changes in a sentence, max 50 chars.
More detailed comments:
+ Changes that have been added.
- Changes that been removed.
Related PR: https://github.com/ginkgo-project/ginkgo/pull/<PR-number>

You can refer to this informative guide for more details.

### Attributing credit

Git has a nice feature where it allows you to add a co-author for your commit, if you would like to attribute credits for the changes made in the commit. This can be done by:

Commit message.
Co-authored-by: Name <email@domain>

In the Ginkgo commit history, this is most common associated with suggested improvements from code reviews.

## Creating, Reviewing and Merging Pull Requests

- The develop branch is the default branch to submit PR's to. From time to time, we merge the develop branch to the main branch and create tags on the main to create new releases of Ginkgo. Therefore, all pull requests must be merged into develop.
- Please have a look at the labels and make sure to add the relevant labels.
- You can mark the PR as a WIP if you are still working on it, Ready for Review when it is ready for others to review it.
- Assignees to the PR should be the ones responsible for merging that PR. Currently, it is only possible to assign members within the ginkgo-project.
- Each pull request requires at least two approvals before merging.
- PR's created from within the repository will automatically trigger two CI pipelines on pushing to the branch from the which the PR has been created. The Github Actions pipeline tests our framework on Mac OSX and on Windows platforms. Another comprehensive Linux based pipeline is run from a mirror on gitlab and contains additional checks like static analysis and test coverage.
- Once a PR has been approved and the build has passed, one of the reviewers can mark the PR as READY TO MERGE. At this point the creator/assignee of the PR needs to verify that the branch is up to date with develop and rebase it on develop if it is not.

# Code style

## Automatic code formatting

Ginkgo uses pre-commit to automatically apply code formatting when committing changes to git. What formatting is applied is managed through ClangFormat with a custom .clang-format configuration file (mostly based on ClangFormat's Google style). Make sure you have pre-commit set up and running properly before committing anything that will end up in a pull request against ginkgo-project/ginkgo repository. In addition, you should never modify the .clang-format configuration file shipped with Ginkgo. E.g. if ClangFormat has trouble reading this file on your system, you should install a newer version of ClangFormat, and avoid commenting out parts of the configuration file.

ClangFormat is the primary tool that helps us achieve a uniform look of Ginkgo's codebase, while reducing the learning curve of potential contributors. However, ClangFormat configuration is not expressive enough to incorporate the entire coding style, so there are several additional rules that all contributed code should follow.

Note: To learn more about how ClangFormat will format your code, see existing files in Ginkgo, .clang-format configuration file shipped with Ginkgo, and ClangFormat's documentation.

## Naming scheme

### Filenames

Filenames use snake_case and use the following extensions:

- C++ source files: .cpp
- C++ header files: .hpp
- CUDA source files: .cu
- CUDA header files: .cuh
- HIP source files: .hip.cpp
- HIP header files: .hip.hpp
- Common source files used by both CUDA and HIP: .hpp.inc
- CMake utility files: .cmake
- Shell scripts: .sh

Note: A C++ source/header file is considered a CUDA file if it contains CUDA code that is not guarded with #if guards that disable this code in non-CUDA compilers. I.e. if a file can be compiled by a general C++ compiler, it is not considered a CUDA file.

### Macros

Macros (both object-like and function-like macros) use CAPITAL_CASE. They have to start with GKO_ to avoid name clashes (even if they are #undef-ed in the same file!).

### Variables

Variables use snake_case.

### Constants

Constants use snake_case.

### Functions

Functions use snake_case.

### Structures and classes

Structures and classes which do not experience polymorphic behavior (i.e. do not contain virtual methods, nor members which experience polymorphic behavior) use snake_case.

All other structures and classes use CamelCase.

### Members

All structure / class members use the same naming scheme as they would if they were not members:

- methods use the naming scheme for functions
- data members the naming scheme for variables or constants
- type members for classes / structures

Additionally, non-public data members end with an underscore (_).

### Namespaces

Namespaces use snake_case.

### Template parameters

- Type template parameters use CamelCase, for example ValueType.
- Non-type template parameters use snake_case, for example subwarp_size.

## Whitespace

Spaces and tabs are handled by ClangFormat, but blank lines are only partially handled (the current configuration doesn't allow for more than 2 blank lines). Thus, contributors should be aware of the following rules for blank lines:

1. Top-level statements and statements directly within namespaces are separated with 2 blank lines. The first / last statement of a namespace is separated by two blank lines from the opening / closing brace of the namespace.
   1. exception: if the first or the last statement in the namespace is another namespace, then no blank lines are required example: ```c++ namespace foo {

        struct x {
        };

        }  // namespace foo

        namespace bar {
        namespace baz {

        void f();

        }  // namespace baz
        }  // namespace bar
        ```

    2.  _exception_: in header files whose only purpose is to _declare_ a bunch
        of functions (e.g. the `*_kernel.hpp` files) these declarations can be
        separated by only 1 blank line (note: standard rules apply for all other
        statements that might be present in that file)
    3.  _exception_: "related" statement can have 1 blank line between them.
        "Related" is not a strictly defined adjective in this sense, but is in
        general one of:

        1.  overload of a same function,
        2.  function / class template and it's specializations,
        3.  macro that modifies the meaning or adds functionality to the
            previous / following statement.

        However, simply calling function `f` from function `g` does not imply
        that `f` and `g` are "related".

1. Statements within structures / classes are separated with 1 blank line. There are no blank lines between the first / last statement in the structure / class.

   1. exception: there is no blank line between an access modifier (private, protected, public) and the following statement. example: ```c++ class foo { public: int get_x() const noexcept { return x_; }

      int &get_x() noexcept { return x_; }

      private: int x_; }; ```

2. Function bodies cannot have multiple consecutive blank lines, and a single blank line can only appear between two logical sections of the function.
3. Unit tests should follow the AAA pattern, and a single blank line must appear between consecutive "A" sections. No other blank lines are allowed in unit tests.
4. Enumeration definitions should have no blank lines between consecutive enumerators.

## Include statement grouping

The concrete ordering will be done by clang-format. Here are the rules that clang-format will follow. In general, all include statements should be present on the top of the file, ordered in the following groups, with one blank lines between each group:

1. Main header file (e.g. core/foo/bar.hpp included in core/foo/bar.cpp, or in the unit testcore/test/foo/bar.cpp)
2. Standard library headers (e.g. vector)
3. Executor specific library headers (e.g. omp.h)
4. System third-party library headers (e.g. papi.h)
5. Public Ginkgo headers
6. Local headers

Example: A file core/base/my_file.cpp might have an include list like this:

#include "ginkgo/core/base/my_file.hpp"
#include <algorithm>
#include <vector>
#include <tuple>
#include <omp.h>
#include <papi.h>
#include <third_party/blas/cblas.hpp>
#include <third_party/lapack/lapack.hpp>
#include <ginkgo/core/base/executor.hpp>
#include <ginkgo/core/base/lin_op.hpp>
#include <ginkgo/core/base/types.hpp>
#include "core/base/my_file_kernels.hpp"

### Main header

This section presents the handling of the main header attributed to a file. For a given file, the main header is the header that contains the declarations of the functions, classes, etc., which are implemented in this file. In the previous example, this would be #include "ginkgo/core/base/my_file.hpp". The clang-format tool figures out the main header. The only intervention form a contributor is to always include the main header using "...".

Please note that this only applies to implementation files, so files ending in .cpp or .cu.

### Some general comments.

1. Private headers of Ginkgo should not be included within the public Ginkgo header.
2. It is a good idea to keep the headers self-sufficient, See Google Style guide for reasoning. When compiling with GINKGO_CHECK_CIRCULAR_DEPS enabled, this property is explicitly checked.
3. The recommendations of the iwyu (Include what you use) tool can be used to make sure that the headers are self-sufficient and that the compiled files ( .cu, .cpp, .hip.cpp ) include only what they use. A CI pipeline is available that runs with the iwyu tool. Please be aware that this tool can be incorrect in some cases.

## Other Code Formatting not handled by ClangFormat

### Control flow constructs

Single line statements should be avoided in all cases. Use of brackets is mandatory for all control flow constructs (e.g. if, for, while, ...).

### Variable declarations

C++ supports declaring / defining multiple variables using a single type-specifier. However, this is often very confusing as references and pointers exhibit strange behavior:

template <typename T> using pointer = T *;
int * x, y; // x is a pointer, y is not
pointer<int> x, y; // both x and y are pointers

For this reason, always declare each variable on a separate line, with its own type-specifier.

## CMake coding style

### Whitespaces

All alignment in CMake files should use four spaces.

### Use of macros vs functions

Macros in CMake do not have a scope. This means that any variable set in this macro will be available to the whole project. In contrast, functions in CMake have local scope and therefore all set variables are local only. In general, wrap all piece of algorithms using temporary variables in a function and use macros to propagate variables to the whole project.

### Naming style

All Ginkgo specific variables should be prefixed with a GINKGO_ and all functions by ginkgo_.

# Helper scripts

To facilitate easy development within Ginkgo and to encourage coders and scientists who do not want get bogged down by the details of the Ginkgo library, but rather focus on writing the algorithms and the kernels, Ginkgo provides the developers with a few helper scripts.

## Create a new algorithm

A create_new_algorithm.sh script is available for developers to facilitate easy addition of new algorithms. The options it provides can be queried with

./create_new_algorithm.sh --help

The main objective of this script is to add files and boiler plate code for the new algorithm using a model and an instance of that model. For example, models can be any one of factorization, matrix, preconditioner or solver. For example to create a new solver named my_solver similar to gmres, you would set the ModelType to solver and set the ModelName to gmres. This would duplicate the core algorithm and kernels of the gmres algorithm and replace the naming to my_solver. Additionally, all the kernels of the new my_solver are marked as GKO_NOT_IMPLEMENTED. For easy navigation and .txt file is created in the folder where the script is run, which lists all the TODO's. These TODO's can also be found in the corresponding files.

## Converting CUDA code to HIP code

We provide a cuda2hip script that converts cuda kernel code into hip kernel code. Internally, this script calls the hipify script provided by HIP, converting the CUDA syntax to HIP syntax. Additionally, it also automatically replaces the instances of CUDA with HIP as appropriate. Hence, this script can be called on a Ginkgo CUDA file. You can find this script in the dev_tools/scripts/ folder.

# Writing Tests

Ginkgo uses the GTest framework for the unit test framework within Ginkgo. Writing good tests are extremely important to verify the functionality of the new code and to make sure that none of the existing code has been broken.

## Testing know-how

- GTest provides a comprehensive documentation of the functionality available within Gtest.
- Reduce code duplication with Testing Fixtures, TEST_F
- Write templated tests using TYPED_TEST.

## Some general rules.

- Unit tests must follow the KISS principle.
- Unit tests must follow the AAA pattern, and a single blank line must appear between consecutive "A" sections.

## Writing tests for kernels

- Reference kernels, kernels on the ReferenceExecutor, are meant to be single threaded reference implementations. Therefore, tests for reference kernels need to be performed with data that can be as small as possible. For example, matrices lesser than 5x5 are acceptable. This allows the reviewers to verify the results for exactness with tools such as MATLAB.
- OpenMP, CUDA, HIP and DPC++ kernels have to be tested against the reference kernels. Hence data for the tests of these kernels can be generated in the test files using helper functions or by using external files to be read through the standard input. In particular for CUDA, HIP and DPC++ the data size should be at least bigger than the architecture's warp size to ensure there is no corner case in the kernels.

# Documentation style

Documentation uses standard Doxygen.

## Developer targeted notes

Make use of @internal doxygen tag. This can be used for any comment which is not intended for users, but is useful to better understand a piece of code.

## Whitespaces

### After named tags such as @param foo

The documentation tags which use an additional name should be followed by two spaces in order to better distinguish the text from the doxygen tag. It is also possible to use a line break instead.

## Documenting examples

There are two main steps:

1. First, you can just copy over the doc/ folder (you can copy it from the example most relevant to you) and adapt your example names and such, then you can modify the actual documentation.

- In tooltip: A short description of the example.
- In short-intro: The name of the example.
- In results.dox: Run the example and write the output you get.
- In kind: The kind of the example. For different kinds see the documentation. Examples can be of basic, techniques, logging, stopping_criteria or preconditioners. If your example does not fit any of these categories, feel free to create one.
- In intro.dox: You write an explanation of your code with some introduction similar to what you see in an existing example most relevant to you.
- In builds-on: You write the examples it builds on.

1. You also need to modify the examples.hpp.in file. You add the name of the example in the main section and in the section that you specified in the doc/kind file in the example documentation.

# Other programming comments

## C++ standard stream objects

These are global objects and are shared inside the same translation unit. Therefore, whenever its state or formatting is changed (e.g. using std::hex or floating point formatting) inside library code, make sure to restore the state before returning the control to the user. See this stackoverflow question for examples on how to do it correctly. This is extremely important for header files.

## Warnings

By default, the -DCMAKE_CXX_FLAGS should be set to -Wpedantic to emit pedantic warnings by default. The CI system additionally also has a step where it compiles for pedantic warnings to be errors.

## Avoiding circular dependencies

To facilitate finding circular dependencies issues (see Using library classes for more details), a CI step no-circular-deps was created. For more details on its usage, see this pipeline, where Ginkgo did not abide to this policy and PR #278 which fixed this. Note that doing so is not enough to guarantee with 100% accuracy that no circular dependency is present. For an example of such a case, take a look at this pipeline where one of the compiler setups detected an incorrect dependency of the cuda module (due to jacobi) on the core module.