In the Ginkgo project, we develop high performance numerical linear algebra functionality reflecting the parallelism of modern HPC platforms. The focus is on GPU-accelerated systems, and Ginkgo can currently be used on AMD GPUs, Intel GPUs, and NVIDIA GPUs using backends written in the respective vendor languages. Ginkgo features a variety of iterative Krylov solvers, sophisticated preconditioners exposing fine-grain parallelism, including incomplete factorizations, incomplete sparse approximate inverses and algebraic multigrid technology, mixed precision algorithms, and preconditioned batched iterative solvers.
Ginkgo is implemented in modern C++ and features interfaces to several popular simulation frameworks, including MFEM, SUNDIALS, deal.ii, HyTeg, openCARP, and OpenFOAM. The Ginkgo library is open source and licensed under BSD 3-clause. In the development of Ginkgo, we aim for industry-level code quality standards, including Continuous Integration (CI) and Continuous Benchmarking (CB), comprehensive unit test coverage, and fulfilling the community policies of the extreme-scale Scientific Software Development Kit (xSDK) and the Extreme Scale Scientific Software Stack (E4S).
Find out more at https://ginkgo-project.github.io