Large-scale parallel computation can be an enabling resource in many areas of engineering and science if the parallel simulation algorithm attains an appreciable fraction of the machine peak performance, and if undue cost in porting the code or in developing the code for the parallel machine is not
Parallel computation of 3-D electromagnetic scattering using finite elements
β Scribed by A. Chatterjee; J. L. Volakis; D. Windheisser
- Publisher
- John Wiley and Sons
- Year
- 1994
- Tongue
- English
- Weight
- 910 KB
- Volume
- 7
- Category
- Article
- ISSN
- 0894-3370
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β¦ Synopsis
The finite element method (FEM) with local absorbing boundary conditions has been recently applied to compute electromagnetic scattering from large 3-D geometries. In this paper, we present details pertaining to code implementation and optimization. Various types of sparse matrix storage schemes are discussed and their performance is examined in terms of vectorization and net storage requirements. The system of linear equations is solved using a preconditioned biconjugate gradient (BCG) algorithm and a fairly detailed study of existing point and block preconditioners (diagonal and incomplete LU) is carried out. A modified ILU preconditioning scheme is also introduced which works better than the traditional version for our matrix systems. The parallelization of the iterative sparse solver and the matrix generation/assembly as implemented on the KSRl multiprocessor is described and the interprocessor communication patterns are analysed in detail. Near-linear speed-up is obtained for both the iterative solver and the matrix generationlassembly phases. Results are presented for a problem having 224,476 unknowns and validated by comparison with measured data.
< I =s 2 storage) quickly become unmanageable in terms of storage and solution time. Another concern while solving problems having more than 100,000 unknowns-a scenario that can be envisioned for most practical problems-is to avoid software bottlenecks. The algorithmic complexity of any part of the program should increase at most linearly with the number of unknowns.
In this paper, the implementation details of our finite element code are presented along with
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