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A parallel algorithm for the two-dimensional time fractional diffusion equation with implicit difference method.

Chunye GongWeimin BaoGuojian TangYuewen JiangJie Liu
Published in: TheScientificWorldJournal (2014)
It is very time consuming to solve fractional differential equations. The computational complexity of two-dimensional fractional differential equation (2D-TFDE) with iterative implicit finite difference method is O(M(x)M(y)N(2)). In this paper, we present a parallel algorithm for 2D-TFDE and give an in-depth discussion about this algorithm. A task distribution model and data layout with virtual boundary are designed for this parallel algorithm. The experimental results show that the parallel algorithm compares well with the exact solution. The parallel algorithm on single Intel Xeon X5540 CPU runs 3.16-4.17 times faster than the serial algorithm on single CPU core. The parallel efficiency of 81 processes is up to 88.24% compared with 9 processes on a distributed memory cluster system. We do think that the parallel computing technology will become a very basic method for the computational intensive fractional applications in the near future.
Keyphrases
  • machine learning
  • deep learning
  • neural network
  • magnetic resonance imaging
  • big data
  • computed tomography
  • magnetic resonance
  • working memory
  • image quality