Proceedings ArticleDOI
Simulating anomalous diffusion on graphics processing units
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TLDR
A GPU implementation of an application for the simulation of diffusion processes using random fractal structures is presented, showing how the irregular computational structure that is inherent to the application can be implemented efficiently in the regular computing environment of a GPU.Abstract:
The computational power of modern graphics processing units (GPUs) has become an interesting alternative in high performance computing. The specialized hardware of GPUs delivers a high degree of parallelism and performance. Various applications in scientific computing have been implemented such that computationally intensive parts are executed on GPUs. In this article, we present a GPU implementation of an application for the simulation of diffusion processes using random fractal structures. It is shown how the irregular computational structure that is inherent to the application can be implemented efficiently in the regular computing environment of a GPU. Performance results are shown to demonstrate the benefits of the chosen implementation approaches.read more
Citations
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Journal ArticleDOI
An embarrassingly parallel algorithm for random walk simulations on random fractal structures
Jens Lang,Janett Prehl +1 more
TL;DR: A parallel algorithm for simulating random walks on fractal structures that is suitable for a wide variety of hardware architectures and the degree of parallelism of the algorithm equals the number of random walkers, which is achieved by its communication-avoiding design.
Journal ArticleDOI
Random walks of oriented particles on fractals
TL;DR: In this article, the effect of the local surrounding fractal structure and the particle orientation on the dynamics of random walks of point particles on fractals has been analyzed, where the anomalous diffusion exponent is smaller than one and the corresponding random walk dimension is larger than two.
Journal ArticleDOI
Accelerating Physical Simulations Using Graphics Processing Units
TL;DR: The hardware architecture of graphics processors and different frameworks for graphics processor programming, such as CAL, Brook+, CUDA and OpenCL with their specific properties, are presented and an overview of different physical applications that have been implemented successfully on graphics processors is given.
References
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Journal ArticleDOI
The random walk's guide to anomalous diffusion: a fractional dynamics approach
Ralf Metzler,Joseph Klafter +1 more
TL;DR: Fractional kinetic equations of the diffusion, diffusion-advection, and Fokker-Planck type are presented as a useful approach for the description of transport dynamics in complex systems which are governed by anomalous diffusion and non-exponential relaxation patterns.
GPU Computing
TL;DR: The background, hardware, and programming model for GPU computing is described, the state of the art in tools and techniques are summarized, and four GPU computing successes in game physics and computational biophysics that deliver order-of-magnitude performance gains over optimized CPU applications are presented.
Journal ArticleDOI
Parallel Computing Experiences with CUDA
Michael Garland,S. Le Grand,John R. Nickolls,Joshua A. Anderson,J. Hardwick,S. Morton,E. Phillips,Yao Zhang,Vasily Volkov +8 more
TL;DR: Experiences gained in applying CUDA to a diverse set of problems are surveyed and the parallel speedups over sequential codes running on traditional CPU architectures attained by executing key computations on the GPU are surveyed.
Journal ArticleDOI
GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model
TL;DR: The critical temperature of the 2D and 3D Ising model is calculated using finite size scaling techniques and an implementation of the checkerboard algorithm on a GPU is able to generate results up to 35 times faster than on a current CPU core.