High-performance Computation and Visualization of Plasma Turbulence on Graphics Processors

Direct numerical simulation (DNS) of turbulence is computationally very intensive and typically relies on some form of parallel processing. Spectral kernels used for spatial discretization are a common computational bottleneck on distributed memory architectures. One way to increase the efficiency of DNS algorithms is to parallelize spectral kernels using tightlycoupled Single-Program-Multiple-Data (SPMD) multiprocessor units with minimal inter-processor communication latency. We present techniques to map DNS computations to modern Graphics Processing Units (GPUs), which are characterized by a very high memory bandwidth and hundreds of SPMD processors. We compare and contrast the performance of our parallel algorithm running on a GPU versus the associated CPU implementation of a solver for one of the fundamental nonlinear models of turbulence theory. We also demonstrate a prototype of a scalable computational steering framework based on turbulence simulation and visualization coupling on the GPU.