A lot of blood, sweat, and tears has gone into OpenMDAO over the years. The project planning started in 2007, coding started in 2008, and our first release came in 2010. We’ve been through three major versions of the code:
- V0 (2010-2013): our first attempt! Serial, with a really awkward API. This was the playground where we really found the core ideas that would power OpenMDAO!
- V1 (2013-2017): OpenMDAO, now with parallel computing and a decent API! This was the first version of OpenMDAO to work in parallel, but we sacrificed serial performance to get there.
- V2 (2017-[a long time into the future]): Awesome performance for both serial AND parallel models, plus an even better API.
With the release of OpenMDAO V2, we finally achieved flexible framework that was efficient for serial and parallel problems. So we finally wrote an overview paper for the framework, and its recently been accepted for publication in the Journal of Structural and Multidisciplinary Optimization. You can find the pre-print here.
There is a bit of something for everyone in this paper. There is a high-level overview of the framework, including how implicit and explicit components leverage the underlying core APIs to support multidisciplinary modeling. There is a walk-through example of how some of the key underlying mathematics of the framework are used and how analytic derivatives are computed. Lastly, there are examples of how and when to use some of the specialized algorithms for computing derivatives efficiently for different kinds of problems.
We hope the paper helps you understand the framework better, and most importantly, helps you to solve some really nice MDO problems!
