Data structures in Java for matrix computations Export

@article{citeulike:1236979, abstract = {In this paper we show how to utilize Java's native arrays for matrix computations. The disadvantages of Java arrays used as a 2D array for dense matrix computation are discussed and ways to improve the performance are examined. We show how to create efficient dynamic data structures for sparse matrix computations using Java's native arrays. This data structure is unique for Java and shown to be more dynamic and efficient than the traditional storage schemes for large sparse matrices. Numerical testing indicates that this new data structure, called Java Sparse Array, is competitive with the traditional Compressed Row Storage scheme on matrix computation routines. Java gives increased flexibility without losing efficiency. Compared with other object-oriented data structures Java Sparse Array is shown to have the same flexibility. Copyright {\copyright} 2004 John Wiley \& Sons, Ltd.}, address = {Department of Informatics, University of Bergen, Norway}, author = {Gundersen, Geir and Steihaug, Trond}, citeulike-article-id = {1236979}, citeulike-linkout-0 = {http://dx.doi.org/10.1002/cpe.793}, citeulike-linkout-1 = {http://www3.interscience.wiley.com/cgi-bin/abstract/109060961/ABSTRACT}, doi = {10.1002/cpe.793}, journal = {Concurrency and Computation: Practice and Experience}, keywords = {matrix-storage}, number = {8}, pages = {799--815}, posted-at = {2007-04-19 14:35:43}, priority = {2}, title = {Data structures in Java for matrix computations}, url = {http://dx.doi.org/10.1002/cpe.793}, volume = {16}, year = {2004} }

TY - JOUR ID - citeulike:1236979 L3 - citeulike-article-id:1236979 N2 - In this paper we show how to utilize Java's native arrays for matrix computations. The disadvantages of Java arrays used as a 2D array for dense matrix computation are discussed and ways to improve the performance are examined. We show how to create efficient dynamic data structures for sparse matrix computations using Java's native arrays. This data structure is unique for Java and shown to be more dynamic and efficient than the traditional storage schemes for large sparse matrices. Numerical testing indicates that this new data structure, called Java Sparse Array, is competitive with the traditional Compressed Row Storage scheme on matrix computation routines. Java gives increased flexibility without losing efficiency. Compared with other object-oriented data structures Java Sparse Array is shown to have the same flexibility. Copyright © 2004 John Wiley & Sons, Ltd. IS - 8 JF - Concurrency and Computation: Practice and Experience AD - Department of Informatics, University of Bergen, Norway EP - 815 TI - Data structures in Java for matrix computations VL - 16 SP - 799 KW - matrix-storage AU - Gundersen, Geir AU - Steihaug, Trond PY - 2004/// UR - http://dx.doi.org/10.1002/cpe.793 ER -