A Novel Compressing a Sparse Matrix using Folding Technique

• Published in: Research Journal of Applied Sciences, Engineering and Technology Vol. 14; no. 8; pp. 310 - 319
• Main Authors: Alabaichi, Ashwak, Alhusiny, Amjad Hamead, Mohammed Thabit, Elham
• Format: Journal Article
• Language: English
• Published: Maxwell Science Publishing 15.08.2017
• Subjects: sparse matrix; transformation; Coding; dense matrix; unfolding; folding
• DOI: 10.19026/rjaset.14.4955
• ISSN: 2040-7467; 2040-7459

There are many application problems that emerge in the areas of engineering simulations, scientific computing, information retrieval and economics which use matrixes where non-zero elements are a significant minority with less than 10%. These are universal in many mathematical and scientific applications. These matrixes enable the reduction of storage and computational requirements by storing and carrying out arithmetic with, only the non-zero elements. This is the sparse matrix which must be compressed for these applications. The sparse matrix compression represents non-zero matrix entries. This study presents a novel algorithm for compressing a sparse matrix, which involves three steps. Firstly it involves the division of sparse matrix into sub-matrixes; secondly conducting several transformations; finally coding them. The novel algorithm is called folding. The compressed matrix reduces memory requirement with a good rate compared with the original sparse matrix. C++ is used in the implementation of this algorithm.