The AFiD code, an open source solver for the incompressible Navier-Stokes equations (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-Bénard 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. PROGRAM SUMMARYProgram Title: AFiD-GPU Licensing provisions(please choose one): GPLv3 Programming language: Fortan 90, CUDA Fortan, MPI External routines: PGI, CUDA Toolkit, FFTW3, HDF5 Nature of problem(approx. 50-250 words): Solving the three-dimensional Navier-Stokes equations coupled with a scalar field in a cubic box bounded between two walls and other four periodic boundaries. Solution method(approx. 50-250 words): Second order finite difference method for spatial discretization, third order Runge-Kutta scheme and Crank-Nicolson method for time advancement, two dimensional pencil distributed MPI parallelization, GPU accelerated routines. Additional comments including Restrictions and Unusual features (approx. 50-250 words): The open-source code is supported and updated on http://www.afid.eu.

We describe the porting of PWscf (Plane-Wave Self Consistent Field), a key component of the Quantum ESPRESSO open-source suite of codes for materials modeling, to GPU systems using CUDA Fortran. Kernel loop directives (CUF kernels) have been extensively used in order to have a single source code for both CPU and GPU implementations. The results of the GPU version have been carefully validated and the performance of the code on several GPU systems (both x86 and POWER8 based) has been compared with traditional Intel multi-core (CPU only) systems. This current GPU version can reduce the timeto-solution by an average factor of 2 − 3 running two different input cases widely used as benchmarks on small and large high performance computing systems.

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