Parallel implementation of complexity reduction approach to fourth order approximation on 2D free space wave propagation.

Recently, a new variant of FDTD method known as High Speed Low Order FDTD (HSLO-FDTD) shows to solve 1D electromagnetic problem faster than the standard FDTD method by 67%. Application of parallel strategy to the method for 2D electromagnetic problem gain better saving in computational time to the parallel FDTD method by 85.2%. This method is called Ultra High Speed Low Order FDTD (UHSLO-FDTD). Both method applies the second order discretization with complexity reduction approach. In this paper, fourth order discretization with complexity reduction approach have succeeds to improve the accuracy of UHSLO-FDTD method. However, the fourth order scheme need higher computational time than UHSLO-FDTD method, but still faster than the FDTD method. This fourth order scheme is called Ultra High Speed High Order Finite Difference Time Domain (UHSHO-FDTD) method. In this paper we solve 2D wave propagation problems on a Symmetrical Multiprocessor machine using message-passing interface. We examine the parallelism efficiency of the algorithm by analyzing the simulation time and speedup

Efficient Parallel Algorithm For Direct Numerical Simulation of Turbulent Flows

A distributed algorithm for a high-order-accurate finite-difference approach to the direct numerical simulation (DNS) of transition and turbulence in compressible flows is described. This work has two major objectives. The first objective is to demonstrate that parallel and distributed-memory machines can be successfully and efficiently used to solve computationally intensive and input/output intensive algorithms of the DNS class. The second objective is to show that the computational complexity involved in solving the tridiagonal systems inherent in the DNS algorithm can be reduced by algorithm innovations that obviate the need to use a parallelized tridiagonal solver

Thermal and hydrodynamic effects in the ordering of lamellar fluids

Phase separation in a complex fluid with lamellar order has been studied in the case of cold thermal fronts propagating diffusively from external walls. The velocity hydrodynamic modes are taken into account by coupling the convection-diffusion equation for the order parameter to a generalised Navier-Stokes equation. The dynamical equations are simulated by implementing a hybrid method based on a lattice Boltzmann algorithm coupled to finite difference schemes. Simulations show that the ordering process occurs with morphologies depending on the speed of the thermal fronts or, equivalently, on the value of the thermal conductivity {\xi}. At large value of {\xi}, as in instantaneous quenching, the system is frozen in entangled configurations at high viscosity while consists of grains with well ordered lamellae at low viscosity. By decreasing the value of {\xi}, a regime with very ordered lamellae parallel to the thermal fronts is found. At very low values of {\xi} the preferred orientation is perpendicular to the walls in d = 2, while perpendicular order is lost moving far from the walls in d = 3.Comment: 8 pages, 3 figures. Accepted for publication in Phil. Trans. of Royal Soc, Ser

libEMM: A fictious wave domain 3D CSEM modelling library bridging sequential and parallel GPU implementation

This paper delivers a software -- libEMM -- for 3D controlled-source electromagnetics (CSEM) modelling in fictitious wave domain, based on the newly developed high-order finite-difference time-domain (FDTD) method on non-uniform grid. The numerical simulation can be carried out over a number of parallel processors using MPI-based high performance computing architecture. The FDTD kernel coded in C has been parallelized with OpenMP for speedup using local shared memory. In addition, the software features a GPU implementation of the same algorithm based on CUDA programming language, which can be cross-validated and compared in terms of efficiency. A perspective of libEMM on the horizon is its application to 3D CSEM inversion in land and marine environment