On the conditions necessary for removing abstraction penalties in OoLALA
OoLALA is an object-oriented linear algebra library designed to reduce the effort of software development and maintenance. In contrast with traditional (Fortran-based) libraries, it provides two high abstraction levels that significantly reduce the number of implementations necessary for particular linear algebra operations. Initial performance evaluations of a Java implementation of OoLALA show that the two high abstraction levels are not competitive with the low abstraction level of traditional libraries. These initial performance results motivate the present contribution-the characterization of a set of storage formats (data structures) and matrix properties (special features) for which implementations at the two high abstraction levels can be transformed into implementations at the low (more efficient) abstraction level. Copyright (c) 2005 John Wiley & Sons, Ltd.
abstraction penalty java object-oriented programming numerical linear algebra