• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.13 no.1
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• pp.13-20
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• 2009

The IPSAP which is a finite element analysis program has been developed for high parallel performance computing. This program consists of various analysis modules - stress, vibration and thermal analysis module, etc. The M orthogonal block Lanczos algorithm with shiftinvert transformation is used for solving eigenvalue problems in the vibration module. And the multifrontal algorithm which is one of the most efficient direct linear equation solvers is applied to factorization and triangular system solving phases in this block Lanczos iteration routine. In this study, the performance enhancement procedures of the IPSAP are composed of the following stages: 1) communication volume minimization of the factorization phase by modifying parallel matrix subroutines. 2) idling time minimization in triangular system solving phase by partial inverse of the frontal matrix and the LCM (least common multiple) concept.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.163-169
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• 2006

In order to use parallel computers in specific applications, algorithms need to be developed and mapped onto parallel computer architectures. Main memory access for shared memory system or global communication in message passing system deteriorate the computation speed. In this paper, it is found that the m-step generalization of the block Lanczos method enhances parallel properties by forming in simultaneous search direction vector blocks. QR factorization, which lowers the speed on parallel computers, is not necessary in the m-step block Lanczos method. The m-step method has the minimized synchronization points, which resulted in the minimized global communications and main memory access compared to the standard methods.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.13-16
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• 2005

It would be desirable to have methods for specific problems, which have low communication costs compared to the computation costs, and in specific applications, algorithms need to be developed and mapped onto parallel computer architectures. Main memory access for shared memory system or global communication in message passing system deteriorate the computation speed. In this paper, it is found that the m-step generalization of the block Lanczos method enhances parallel properties by forming m simultaneous search direction vector blocks. QR factorization, which lowers the speed on parallel computers, is not necessary in the m-step block Lanczos method. The m-step method has the minimized synchronization points, which resulted in the minimized global communications compared to the standard methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2351-2369
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• 2012

This paper describes interpolation method of motion field in the Wyner-Ziv video coding (WZVC) based on Expectation-Maximization (EM) algorithm. In the EM algorithm, the estimated motion field distribution is calculated on a block-by-block basis. Each pixel in the block shares similar probability distribution, producing an undesired blocking artefact on the pixel-based motion field. The proposed interpolation techniques are Bicubic and Lanczos which successively use 16 and 32 neighborhood probability distributions of block-based motion field for one pixel in k-by-k block on pixel-based motion field. EM-based WZVC codec updates the estimated probability distribution on block-based motion field, and interpolates it to pixel resolution. This is required to generate higher-quality soft side information (SI) such that the decoding algorithm is able to make syndrome estimation more quickly. Our experiments showed that the proposed interpolation methods have the capability to reduce EM-based WZVC decoding complexity with small increment of bit rate.

• Interaction and multiscale mechanics
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• v.1 no.2
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• pp.211-230
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• 2008

Owing to the growing size of the eigenvalue problem and the growing number of eigenvalues desired, solution methods of iterative nature are becoming more popular than ever, which however suffer from low efficiency and lack of proper convergence criteria. In this paper, three efficient iterative eigenvalue algorithms are considered, i.e., subspace iteration method, iterative Ritz vector method and iterative Lanczos method based on the cell sparse fast solver and loop-unrolling. They are examined under the mode error criterion, i.e., the ratio of the out-of-balance nodal forces and the maximum elastic nodal point forces. Averagely speaking, the iterative Ritz vector method is the most efficient one among the three. Based on the mode error convergence criteria, the eigenvalue solvers are shown to be more stable than those based on eigenvalues only. Compared with ANSYS's subspace iteration and block Lanczos approaches, the subspace iteration presented here appears to be more efficient, while the Lanczos approach has roughly equal efficiency. The methods proposed are robust and efficient. Large size tests show that the improvement in terms of CPU time and storage is tremendous. Also reported is an aggressive shifting technique for the subspace iteration method, based on the mode error convergence criteria. A backward technique is introduced when the shift is not located in the right region. The efficiency of such a technique was demonstrated in the numerical tests.