کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
432822 | 689083 | 2011 | 13 صفحه PDF | دانلود رایگان |

The diffusion–drift algorithm for calculating the electric signals of growing breast cancerous cells is parallelized based on the Message Passing Interface technique. The parallelized algorithm is analyzed with emphasis on the existing bottlenecks. The model involves the solution of several systems of equations to calculate the biopotentials and ion concentration gradients generated by MCF-7 cells, the most studied breast cancer cell line. The Portable, Extensible Toolkit for Scientific Computation library is investigated for the parallel solution of these systems of equations. The results show that the optimum solver for the biopotential system of equations is the Enhanced Bi-Conjugate Gradient Stabilized (L)(L) solver. Also, it is found that the optimum pre-conditioner is the Additive Schwarz Method coupled with the drop tolerance Incomplete LU factorization. A maximum overall speed up of 15 was achieved using 56 processors with an efficiency of 27%. The electrophysiological activity of a tumor a third of a millimeter in size with just over a thousand cancerous cells is simulated. The numerical values of the biopotential could indicate to breast cancer in very early stages.
► The diffusion–drift algorithm for the electric activity of tumors is parallelized.
► A comparison between different parallel solvers is presented.
► The speed up and efficiency of the optimized parallel model are calculated.
► Parallelization allows much more cells than previously reported to be simulated.
Journal: Journal of Parallel and Distributed Computing - Volume 71, Issue 7, July 2011, Pages 1011–1023