Vector models for data-parallel computing
Vector models for data-parallel computing
An updated set of basic linear algebra subprograms (BLAS)
ACM Transactions on Mathematical Software (TOMS)
Exploring New Architectures in Accelerating CFD for Air Force Applications
HPCMP-UGC '08 Proceedings of the 2008 DoD HPCMP Users Group Conference
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
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Modern graphical processing units (GPUs) have recently become a pervasive technology able to rapidly solve large parallel problems which previously required runs on clusters or supercomputers. In this paper we propose an effective strategy to parallelize the T-matrix method on GPUs in order to speed-up light scattering simulations. We have tackled two of the most computationally intensive scattering problems that are of interest in nano-optics: the scattering from an isolated non-axisymmetric particle and from an agglomerate of arbitrary shaped particles. We show that fully exploiting the GPU potential we can achieve more than 20 times (20x) acceleration over sequential execution in the investigated scenarios, opening exciting prospectives in the analysis and the design of optical nanostructures.