1. Introduction of Parallel GPGPU Acceleration Algorithms for the Solution of Radiative Transfer
- Author
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Xu Liu and William F. Godoy
- Subjects
Numerical Analysis ,Computer science ,Monte Carlo method ,Graphics processing unit ,Condensed Matter Physics ,Computer Science Applications ,Computational science ,Computer Science::Performance ,Computer graphics ,Acceleration ,Mechanics of Materials ,Modeling and Simulation ,Computer Science::Mathematical Software ,Radiative transfer ,Central processing unit ,Graphics ,General-purpose computing on graphics processing units ,Algorithm ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
General-purpose computing on graphics processing units (GPGPU) is a recent technique that allows the parallel graphics processing unit (GPU) to accelerate calculations performed sequentially by the central processing unit (CPU). To introduce GPGPU to radiative transfer, the Gauss-Seidel solution of the well-known expressions for 1-D and 3-D homogeneous, isotropic media is selected as a test case. Different algorithms are introduced to balance memory and GPU-CPU communication, critical aspects of GPGPU. Results show that speed-ups of one to two orders of magnitude are obtained when compared to sequential solutions. The underlying value of GPGPU is its potential extension in radiative solvers (e.g., Monte Carlo, discrete ordinates) at a minimal learning curve.
- Published
- 2011
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