An Efficient Parallel Implicit Solver for LOD-FDTD Algorithm in Cloud Computing Environment

This letter presents an efficient parallel algorithm for solving locally one-dimensional (LOD) finite-difference time domain (FDTD) in cloud computing environment. As opposed to the existing LOD-FDTD algorithm parallelization scheme, the proposed method solves the implicit tridiagonal system in parallel by using the Sherman–Morrison formula to decompose the tridiagonal matrix into smaller matrices. The parallel nodes in cloud computers solve the matrices simultaneously. Numerical results show that the proposed method is more efficient in cloud computing environment than the conventional parallelization scheme and shows better scalability.

[1]  Canqun Yang,et al.  MilkyWay-2 supercomputer: system and application , 2014, Frontiers of Computer Science.

[2]  E. L. Tan,et al.  Unconditionally Stable LOD–FDTD Method for 3-D Maxwell's Equations , 2007, IEEE Microwave and Wireless Components Letters.

[3]  Eng Leong Tan.  Acceleration of LOD-FDTD Method Using Fundamental Scheme on Graphics Processor Units , 2010, IEEE Microwave and Wireless Components Letters.

[4]  Zhizhang Chen,et al.  A finite-difference time-domain method without the Courant stability conditions , 1999 .

[5]  D.J. Edwards,et al.  Analysis of Realistic Ultrawideband Indoor Communication Channels by Using an Efficient Ray-Tracing Based Method , 2009, IEEE Transactions on Antennas and Propagation.

[6]  J. Yamauchi,et al.  An LOD-FDTD Method for the Analysis of Periodic Structures at Normal Incidence , 2009, IEEE Antennas and Wireless Propagation Letters.

[7]  F. Teixeira,et al.  Split-field PML implementations for the unconditionally stable LOD-FDTD method , 2006, IEEE Microwave and Wireless Components Letters.

[8]  Hideo Yokota,et al.  Efficient Parallel LOD-FDTD Method for Debye-Dispersive Media , 2014, IEEE Transactions on Antennas and Propagation.

[9]  C. Choi,et al.  Simulation of Axon Activation by Electrical Stimulation— Applying Alternating-Direction-Implicit Finite- Difference Time-Domain Method , 2012, IEEE Transactions on Magnetics.

[10]  A. S. Mohan,et al.  Segmented-Locally-One-Dimensional-FDTD Method for EM Propagation Inside Large Complex Tunnel Environments , 2012, IEEE Transactions on Magnetics.

[11]  Sabine Fenstermacher,et al.  Numerical Approximation Of Partial Differential Equations , 2016 .

[12]  Marios D. Dikaiakos,et al.  Cloud Computing: Distributed Internet Computing for IT and Scientific Research , 2009, IEEE Internet Computing.

[13]  K. Mahdjoubi,et al.  A parallel FDTD algorithm using the MPI library , 2001 .

[14]  Rushan Chen,et al.  An Efficient Domain Decomposition Parallel Scheme for Leapfrog ADI-FDTD Method , 2017, IEEE Transactions on Antennas and Propagation.

[15]  Steven G. Johnson,et al.  Meep: A flexible free-software package for electromagnetic simulations by the FDTD method , 2010, Comput. Phys. Commun..

[16]  Er-Ping Li,et al.  Development of the Three-Dimensional Unconditionally Stable LOD-FDTD Method , 2008, IEEE Transactions on Antennas and Propagation.

[17]  Yao Zhang,et al.  Fast tridiagonal solvers on the GPU , 2010, PPoPP '10.

[18]  Joan-Josep Climent,et al.  A note on the recursive decoupling method for solving tridiagonal linear systems , 2003, Appl. Math. Comput..

[19]  Nikolaos V. Kantartzis,et al.  Parallel LOD-FDTD Method With Error-Balancing Properties , 2015, IEEE Transactions on Magnetics.

[20]  Nikolaos V. Kantartzis,et al.  Accuracy-Adjustable Nonstandard LOD-FDTD Schemes for the Design of Carbon Nanotube Interconnects and Nanocomposite EMC Shields , 2013, IEEE Transactions on Magnetics.