Abstract:

Multidimensional data such as threedimensional position information is one of the major data objects of current high performance computer systems. Its date compression is an important technique to tackle the problem that lack of data storage space and I/O bandwidth cannot meet the demands of rapidly increasing massive multidimensional data. Existing algorithms are insufficient for multidimensional floating data compression. A curve fitting method for massive multidimensional data compression is proposed. Multidimensional floatingpoint data is projected onto a twodimensional coordinates. By using polynomial curve fitting, the original data is compressed by storing the polynomial coefficients. Sorting is introduced in the design of the algorithm as the data preprocessing means; thereby a smaller compression error is obtained. The theoretical analysis and experimental results show that the compression ratio of our proposed algorithm outperforms the existing algorithms with the same error rate.

Key words: multi-dimensional floating data;curve fitting;compression algorithm;storage