Ginkgo Integrations#
Ginkgo is a high-performance numerical linear algebra library for many-core systems, with a focus on the solution of sparse linear systems. It is implemented using modern C++ with GPU kernels for NVIDIA (CUDA), AMD (HIP), and Intel (SYCL) GPUs. The library core contains architecture-agnostic algorithms – iterative solvers, preconditioners, and matrix formats – while runtime polymorphism selects the right architecture-optimized kernel depending on the target hardware.
This site collects self-contained integration examples that demonstrate how Ginkgo can be used as a solver backend inside established scientific computing frameworks. Each example ships with its own build system, source code, and documentation so you can study the approach, build it locally, and adapt it to your own project.
Browse by library#
Finite-element library for adaptive meshes.
Poisson – standard elliptic PDE
Adaptive Refinement – AMR with Ginkgo solvers
Scalable finite-element library with high-order support.
Poisson – basic diffusion problem
High-Order Diffusion – high-order elements
GPU-accelerated spectral-element CFD solver.
Poisson – pressure-like solve
Turbulent Channel – turbulent flow simulation
Suite of nonlinear and differential/algebraic equation solvers.
Poisson (KINSOL) – nonlinear system with Ginkgo linear solver
Stiff ODE (CVODE) – stiff initial-value problem
Compare by problem#
Poisson equation#
The Poisson equation appears in nearly every scientific domain. Compare how each framework formulates the same problem and uses Ginkgo to solve the resulting linear system:
Framework |
Example |
Approach |
|---|---|---|
deal.II |
Continuous Galerkin FEM on adaptive meshes |
|
MFEM |
High-performance FEM with flexible backends |
|
NekRS |
Spectral-element discretization on GPUs |
|
SUNDIALS |
Nonlinear solve (KINSOL) with Ginkgo preconditioner |