J. Gondzio and A. Grothey
Abstract
OOPS is an object oriented parallel solver using the primal-dual
interior point methods. Its main component is an object-oriented
linear algebra library designed to exploit nested block structure
that is often present is truly large-scale optimization problems such
as those appearing in Stochastic Programming.
This is achieved by treating the building blocks of the structured
matrices as objects, that can use their inherent linear algebra
implementations to efficiently exploit their structure both
in a serial and parallel environment. Virtually any nested
block-structure can be exploited by representing the matrices
defining the problem as a tree build from these objects.
OOPS can be run on a wide variety of architectures and has been used
to solve a financial planning problem with over $10^9$ decision
variables.
We give details of supported structures and their
implementations. Further we give details of how parallelisation
is managed in the object-oriented framework.
Key words: Interior Point Methods, Exploiting Structure, Parallel Computing.