  The AFiD code, an open source solver for the incompressible Navier-Stokes
equations ({\color{blue}\burl{http://www.afid.eu}}), has been ported to GPU
clusters to tackle large-scale wall-bounded turbulent flow simulations. The GPU
porting has been carried out in CUDA Fortran with the extensive use of kernel
loop directives (CUF kernels) in order to have a source code as close as
possible to the original CPU version; just a few routines have been manually
rewritten. A new transpose scheme, which is not limited to the GPU version only
and can be generally applied to any CFD code that uses pencil distributed
parallelization, has been devised to improve the scaling of the Poisson solver,
the main bottleneck of incompressible solvers. The GPU version can reduce the
wall clock time by an order of magnitude compared to the CPU version for large
meshes. Due to the increased performance and efficient use of memory, the GPU
version of AFiD can perform simulations in parameter ranges that are
unprecedented in thermally-driven wall-bounded turbulence. To verify the
accuracy of the code, turbulent Rayleigh-B\'enard convection and plane Couette
flow are simulated and the results are in good agreement with the experimental
and computational data that published in previous literatures.
