Geir Gundersen and Trond Steihaug
In this paper it is shown how to utilize Java arrays for matrix computations. We discuss the disadvantages of Java arrays when used as two-dimensional array for dense matrix computation, and how to improve the performance. We show how to create efficient dynamic data structure for sparse matrix computation using Java's native arrays. We construct a data structure for large sparse matrices that is unique for Java. This datastructure is shown to be more dynamic and efficient than the traditional storage schemes for large sparse matrices. Numerical results show that this new data structure, called Java Sparse Array (JSA), is competitive with the traditionally Compressed Row Storage scheme (CRS) on matrix computation routines. Java gives flexibility without loosing efficiency. Compared to other object oriented data structures it is shown that JSA has the same flexibility.
In Norsk Informatikkkonferanse NIK'2002, Kongsberg November 25-27, 2002, pp 97-108, Tapir 2002, ISBN 82-91116-45-8.
