214 research outputs found
Coupled Vlasov and two-fluid codes on GPUs
We present a way to combine Vlasov and two-fluid codes for the simulation of
a collisionless plasma in large domains while keeping full information of the
velocity distribution in localized areas of interest. This is made possible by
solving the full Vlasov equation in one region while the remaining area is
treated by a 5-moment two-fluid code. In such a treatment, the main challenge
of coupling kinetic and fluid descriptions is the interchange of physically
correct boundary conditions between the different plasma models. In contrast to
other treatments, we do not rely on any specific form of the distribution
function, e.g. a Maxwellian type. Instead, we combine an extrapolation of the
distribution function and a correction of the moments based on the fluid data.
Thus, throughout the simulation both codes provide the necessary boundary
conditions for each other. A speed-up factor of around 20 is achieved by using
GPUs for the computationally expensive solution of the Vlasov equation and an
overall factor of at least 60 using the coupling strategy combined with the GPU
computation. The coupled codes were then tested on the GEM reconnection
challenge
A Simple GPU-Accelerated Two-Dimensional MUSCL-Hancock Solver for Ideal Magnetohydrodynamics
We describe our experience using NVIDIA's CUDA (Compute Unified Device Architecture) C programming environment to implement a two-dimensional second-order MUSCL-Hancock ideal magnetohydrodynamics (MHD) solver on a GTX 480 Graphics Processing Unit (GPU). Taking a simple approach in which the MHD variables are stored exclusively in the global memory of the GTX 480 and accessed in a cache-friendly manner (without further optimizing memory access by, for example, staging data in the GPU's faster shared memory), we achieved a maximum speed-up of approx. = 126 for a sq 1024 grid relative to the sequential C code running on a single Intel Nehalem (2.8 GHz) core. This speedup is consistent with simple estimates based on the known floating point performance, memory throughput and parallel processing capacity of the GTX 480
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