Parallel Optimization

Parallel optimization in OPT++ comes in a couple of different forms. The first occurs when traditionally serial methods, such as Newton methods, require finite-difference approximations to the gradient because analytic gradients are not available. In this setting, the gradient evaluations are performed speculatively and in parallel. This is done automatically when the parallel version of OPT++ is built; however, there is some onus on the user who wants to take advantage of this capability. In particular, it is necessary to initialize and finalize MPI and to set up file names or working directories that prevent messy file I/O. The other form of parallelism occurs when the optimization algorithms themselves are parallel. This occurs in three methods included in OPT++: parallel direct search (PDS), a trust region-parallel direct search hybrid (TRPDS) and a generating set search method (GSS). Again, the parallelism is done automatically when the parallel version of OPT++ is built, but the user is required to perform a couple of tasks.

The following examples demonstrate how to make use of the PDS and TRPDS methods. Furthermore, these examples demonstrate the steps required to set up OPT++ to take advantage of its parallel capabilities, whether it be for speculative finite-difference gradient computations or for a parallel optimization algorithm.

Notes: We hope to hide the steps required to set up parallelism in future releases. Also, if the function evaluation is parallel, it currently cannot be used together with OPT++ parallel capabilities. We will be adding support for multi-level parallelism in future releases.

Using a Parallel Optimization Method

  1. Optimizing with a Parallel Direct Search Method
  2. Optimizing with Trust-Region Parallel Direct Search (TRPDS)
  3. Optimizing with a Generating Set Search Method (GSS)

Next Section: Optimization Methods | Back to Main Page

Last revised July 13, 2006

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Documentation, generated by , last revised August 30, 2006.