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Large-scale nonlinear ultrasound simulations using the open-source k-Wave toolbox are now routinely performed using the MPI version of k-Wave running on traditional CPU-based clusters. However, the all-to-all communications required by the 3D fast Fourier transform (FFT) severely impact performance when scaling to large numbers of compute cores. This can be overcome by using a domain decomposition strategy based on a local Fourier basis. In this work, we analyze the performance and accuracy of using local domain decomposition for running a high-intensity focused ultrasound (HIFU) simulation in the kidney on a single server containing eight NVIDIA P40 graphical processing units (GPUs). Different decompositions and overlap sizes are investigated and compared to a global MPI simulation running on a CPU-based supercomputer using 1280 cores. For a grid size of 960 by 960 by 1280 grid points and an overlap size of 4 grid points, the error in the simulation using local domain decomposition is on the order of 0.1$ compared to the global simulation, which is sufficient for most applications. The financial cost for running the simulation is also reduced by more than an order of magnitude.Large-scale nonlinear ultrasound simulations using the open-source k-Wave toolbox are now routinely performed using the MPI version of k-Wave running on traditional CPU-based clusters. However, the all-to-all communications required by the 3D fast Fourier transform (FFT) severely impact performance when scaling to large numbers of compute cores. This can be overcome by using a domain decomposition strategy based on a local Fourier basis. In this work, we analyze the performance and accuracy of using local domain decomposition for running a high-intensity focused ultrasound (HIFU) simulation in the kidney on a single server containing eight NVIDIA P40 graphical processing units (GPUs). Different decompositions and overlap sizes are investigated and compared to a global MPI simulation running on a CPU-based supercomputer using 1280 cores. For a grid size of 960 by 960 by 1280 grid points and an overlap size of 4 grid points, the error in the simulation using local domain decomposition is on the order of 0.1...

Performance and accuracy analysis of nonlinear k-Wave simulations using local domain decomposition with an 8-GPU server