Extended Parallelism Models for Optimization on Massively Parallel Computers
Eldred, B.D. Schimel · 1999
Single-level parallel optimization approaches, those in which either the simulation code executes in parallel or the optimization algorithm invokes multiple simultaneous single-processor analyses, have been investigated previously and have been shown to be effective in reducing the time required to compute optimal solutions. However, these approaches have clear performance limitations that prevent effective scaling with the thousands of processors available in massively parallel supercomputers. In more recent work, a capability has been developed for multilevel parallelism in which multiple instances of multiprocessor simulations are coordinated simultaneously. This implementation employs a master-slave approach using the Message Passing Interface (MPI) within the DAKOTA software toolkit. Mathematical analysis on achieving peak efficiency in multilevel parallelism has shown that the most effective processor partitioning scheme is the one that limits the size of multiprocessor simulatio...