Evaluation of Large-scale Optimization Problems on Vector and Parallel Architectures

The authors examine the importance of problem formulation for the solution of large-scale optimization problems on high-performance architectures. Limited memory variable metric methods are used to illustrate performance issues. It is shown that the performance of these algorithms is drastically affected by application implementation. Model applications are drawn from the MINPACK-2 test problem collection, with numerical results from a super-scalar architecture (IBM RS6000/370), a vector architecture (CRAY-2), and a massively parallel architecture (Intel DELTA).