• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.6
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• pp.377-384
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• 2017

The scope of the matrix application is so broad that it can not be limited. A typical matrix application area in computer science is image processing. Particularly, radar scanning equipment implemented on a small embedded system requires real-time matrix transposition for image processing, and since its memory size is small, a general matrix transposition algorithm can not be applied. In this case, matrix transposition must be done in disk space, such as flash disk, using a limited memory buffer. In this paper, we analyze and improve a recently published flash disk-based matrix transposition algorithm named as asymmetric sub-matrix transposition algorithm. The performance analysis shows that the asymmetric sub-matrix transposition algorithm has lower performance than the conventional sub-matrix transposition algorithm, but the improved asymmetric sub-matrix transposition algorithm is superior to the sub-matrix transposition algorithm in 13 of the 16 experimental data.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.2
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• pp.81-89
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• 2015

In this paper, we proposed a new matrix transposition scheme, called asymmetry sub-matrix, and conducted the in-depth performance evaluation of the proposed scheme with other prior schemes, including element-major, row-major and sub-matrix schemes in large-scale matrix. In our results, the proposed asymmetry sub-matrix scheme shows the best performance compared to other prior schemes, while sub-matrix scheme shows the second best performance.