TAO users manual.
Citations Over Time
Abstract
The Toolkit for Advanced Optimization (TAO) focuses on the design and implementation of component-based optimization software for the solution of large-scale optimization applications on high-performance architectures. Their approach is motivated by the scattered support for parallel computations and lack of reuse of linear algebra software in currently available optimization software. The TAO design allows the reuse of toolkits that provide lower-level support (parallel sparse matrix data structures, preconditioners, solvers), and thus they are able to build on top of these toolkits instead of having to redevelop code. The advantages in terms of efficiency and development time are significant. The TAO design philosophy uses object-oriented techniques of data and state encapsulation, abstract classes, and limited inheritance to create a flexible optimization toolkit. This chapter provides a short introduction to the design philosophy by describing the objectives in TAO and the importance of this design. Since a major concern in the TAO project is the performance and scalability of optimization algorithms on large problems, they also present some performance results.
Related Papers
- → Development of a simulation model for reuse businesses and case studies in Japan(2010)37 cited
- Research on recycle and reuse of auto material(2003)
- Overinheritance and Inadequate Inheritance(2002)
- → HARMONI WARIS ISLAM DAN SUNDA(2015)
- → Research on the Industrial Development System Construction of Contemporary Inheritance of Chinese Traditional Painting Art(2022)