Parallel in-core and out-of-core solution of electrically large problems using the RWG basis functions

Yu Zhang, Mary Taylor, Tapan K. Sarkar, Arijit De, Mengtao Yuan, Hongsik Moon, Changhong Liang

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Currently, the problem size that can be solved in reasonable time using the Method of Moments is limited by the amount of memory installed in the computer. This paper offers a new development that not only breaks this memory constraint, but also maintains the efficiency of running the problem in-core. In this paper, highly efficient parallel matrix-filling schemes are presented for parallel in-core and parallel out-of-core integral-equation solvers with subdomain RWG basis functions. The parallel methodology for matrix filling is quite different when using a subdomain basis as opposed to using a higher-order basis. The parallel in-core solver uses memory, which is often expensive and limited in size. The parallel out-of-core solver is introduced to extend the capability of MoM to solve larger problems that can be as large as the amount of storage on the hard disk. Numerical results on several typical computer platforms show that the parallel matrix-filling schemes and matrix-equation solvers introduced here are highly efficient and achieve theoretical predictions. The implementation of these advancements with the widely used RWG basis functions creates a powerful tool for efficient computational electromagnetics solution of complex real-world problems.

Original languageEnglish (US)
Pages (from-to)84-94
Number of pages11
JournalIEEE Antennas and Propagation Magazine
Issue number5
StatePublished - 2008


  • Computation time
  • Computational electromagnetics
  • Electrically large objects
  • In-core solver
  • Moment methods
  • Outof-core solver
  • Parallel algorithms
  • Parallel architectures
  • Parallel processing
  • Parallel programming
  • Radar cross section

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Electrical and Electronic Engineering


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