Our CFD framework QuICC, based on a fully spectral method, has been successfully used for various dynamo simulations in spherical and Cartesian geometries.It runs efficiently on a few thousands of cores using a 2D data distribution based on a distributed memory paradigm (MPI).In order to better harness the computing power of current and upcoming HPC systems, which are increasingly based on heterogeneous nodes built from multi-core processors and accelerators (GPU), we present our work on refactoring the framework to introduce a hybrid distributed and shared memory parallelization (MPI + X).A critical part of this strategy is the refactorization of the nonlinear transform step.The nonlinear transform step is refactored to be described and manipulated in ''qir'' a bare-bone instruction-oriented language.Though passes, the tree is pruned and optimized, temporary resources and communication grouping is handled programmatically.A visitor pattern is used both for the instantiation and the dispatch of the correct back-ends at runtime.The refactored tree enables QuICC to run full simulations on hybrid machines efficiently.The implementation of ''qir'' and a performance comparison for different back-ends will be presented.