Ginkgo is a high-performance linear algebra library for manycore systems, with a focus on sparse solution of linear systems. It is implemented using modern C++ (you will need at least C++11 compliant compiler to build it), with GPU kernels implemented in CUDA.
An extensive database of up-to-date benchmark results is available in the performance data repository. Visualizations of the database can be interactively generated using the Ginkgo Performance Explorer web application. The benchmark results are automatically updated using the CI system to always reflect the current state of the library.
Linux and Mac OS
For Ginkgo core library:
- cmake 3.9+
- C++11 compliant compiler, one of:
- gcc 5.3+, 6.3+, 7.3+, 8.1+
- clang 3.9+
- Apple LLVM 8.0+ (TODO: verify)
The Ginkgo CUDA module has the following additional requirements:
- CUDA 9.0+
- Any host compiler restrictions your version of CUDA may impose also apply here. For the newest CUDA version, this information can be found in the CUDA installation guide for Linux or CUDA installation guide for Mac Os X
In addition, if you want to contribute code to Ginkgo, you will also need the following:
- clang-format 5.0.1+ (ships as part of clang)
- clang-tidy (optional, when setting the flag
- iwyu (Include What You Use, optional, when setting the flag
Windows is currently not supported, but we are working on porting the library there. If you are interested in helping us with this effort, feel free to contact one of the developers. (The library itself doesn't use any non-standard C++ features, so most of the effort here is in modifying the build system.)
NOTE: Some restrictions will also apply on the version of C and C++ standard libraries installed on the system. This needs further investigation.
To build Ginkgo, you can use the standard CMake procedure.
mkdir build; cd build cmake -G "Unix Makefiles" .. && make
GINKGO_BUILD_REFERENCE is enabled. You should be able to run examples with this
executor. You would need to explicitly compile with the OpenMP and CUDA modules enabled
to run with these executors. Please refer to the Installation page.
After the installation, CMake can find ginkgo with
An example can be found in the
Various examples are available for you to understand and play with Ginkgo within the
examples/ directory. They can be compiled by passing the
-DGINKGO_BUILD_EXAMPLES=ON to the cmake command. Documentation for the examples is available within the
doc/ folder in each of the example directory and a commented code with explanations can found in the online documentation.
Ginkgo does comprehensive unit tests using Google Tests. These tests are enabled by default and can be disabled if necessary by passing the
-DGINKGO_BUILD_TESTS=NO to the cmake command. More details about running tests can be found in the TESTING.md page.
Running the benchmarks
A unique feature of Ginkgo is the ability to run benchmarks and view your results with the help of the Ginkgo Performance Explorer (GPE).
More details about this can be found in the BENCHMARKING.md page
Contributing to Ginkgo
When contributing for the first time, please add yourself to the list of external contributors like in the example below.
I hereby place all my contributions in this codebase under a BSD-3-Clause license, as specified in the repository's LICENSE file.
Name Surname email@domain Institution(s)
Contributing guidelines can be accessed in our Wiki under the Developer's Homepage. This page also contains other information useful to developers, such as writing proper commit messages, understanding Ginkgo's library design, relevant C++ information, and more.
In general, always refer to this page for developer information. If you think that anything is missing, feel free to create an issue.
Ginkgo is available under the 3-clause BSD license. All contributions to the project are added under this license.
Depending on the configuration options used when building Ginkgo, third party software may be pulled as additional dependencies, which have their own licensing conditions. Refer to ABOUT-LICENSING.md for details.