This paper deals with the solution of an inverse time fractional diffusion equation described by a Caputo fractional derivative. Numerical simulations, involving large domains, give rise to a huge practical problem. Hence, by starting from an accurate meshless localized collocation method using radial basis functions (RBFs), here we propose a fast algorithm which exploits the GPU-CUDA capabilities. More in detail, we first developed a C code which uses the well-known numerical library LAPACK to perform basic linear algebra operations in order to implement an efficient sequential algorithm. Then we propose a GPU software based on ad hoc parallel CUDA-kernels and efficient usage of parallel numerical libraries available for GPUs. Performance analysis will show the reliability and the efficiency of the proposed parallel implementation.
|Titolo:||A GPU-CUDA framework for solving a two-dimensional inverse anomalous diffusion problem|
|Data di pubblicazione:||2020|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|