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We propose an approach for high-performance scientific computing that separates the description of algorithms from the generation of code for parallel hardware architectures like Multi-Core CPUs, GPUs or FPGAs. This way, a scientist can focus on his domain of expertise by describing his algorithms generically without the need to have knowledge of specific hardware architectures, programming languages,...
In this paper, GPGPU(the general purpose computing on graphics processing units)-based ADE-FDTD (alternating-direction-explicit finite-difference time-domain) method is proposed for a massively parallel electromagnetic field simulation of large-scale problems. First, the ADE-FDTD method, which is an almost unconditionally stable algorithm, is described briefly. Next, implementation technique of the...
The HIE(Hybrid Implicit-Explicit)-FDTD method is very useful for the simulation of computational domain with thin cells. This paper describes the HIE-FDTD method with GPGPU(General Purpose computing on Graphic Processing Unit) for massively parallel electromagnetic field simulation. First, the properties of the HIE-FDTD method are explained. Next, 3D HIE-FDTD method with CUDA is implemented. Finally,...
Many games and other interactive virtual environments are known for their focus in rendering natural phenomena, such as accurate visuals and physics, in the most believable manner. Several advances in the aforementioned fields took place during the last decade but, unfortunately, this effort has not been reflected in libraries for spatial audio. These libraries traditionally do not accurately simulate...
The scattering of acoustic waves in non-homogeneous media has been of practical interest for the petroleum industry, mainly in the determination of new oil deposits. A family of computational models that represent this phenomenon is based on finite difference methods. The simulation of these phenomena demands a high computational cost. In this work we employ GPU for the development of solvers for...
The method Finite Difference Time Domain (FDTD) is widely used in electromagnetic simulations. Since this method is a data intensive and computation intensive problem, there are a lot of initiatives to improve the scalability and the performance of the FDTD. Specifically the use of GPU to accelerate the FDTD is in focus, which has a good cost-benefit, offering a speedup of hundreds of times if compared...
Simple models of major CPU-intensive MAGIC electromagnetic (EM) plasma code portions using the CUDA language run on the graphical processing unit (GPU) indicate 12x computing rate compared to the same calculations run on the CPU only. MAGIC is being modified for performance speedup of large-scale plasma-wave EM calculations using GPU processing. Results to-date from MAGIC with the particle update...
Recently, the use of graphics processing units as a means of achieving the hardware acceleration of the finite-difference time-domain (FDTD) technique has attracted significant interest in the computational electromagnetics community. However, the large memory requirements of the FDTD, compounded by the limited memory resources available in graphics processing units, compromise the efficiency of this...
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