To deal with the chaotic nature of the real world, researchers use data assimilation as part of any realistic simulation. Data assimilation allows us to modify the simulation results based on the real-world observations and deal with the exponentially growing error.
A year ago the OpenACC organization put out version 3.0 of the specification, a major upgrade that, among other things, moved forward the support for our base languages (C, C++, and Fortran) to their latest versions. The technical committee didn’t stop working though, and I’m pleased to announce the release of OpenACC 3.1 for November 2020. It’s hard to follow a major release like 3.0, but I believe the changes we made this year will help to make OpenACC implementations better, more interoperable, and easier to use with modern C++ and Fortran.
When OpenACC 3.0 was released in November 2019 the most exciting feature, in my opinion at least, is actually one that might easily be overlooked: updating our base languages. If you’re not familiar with this term, the base languages are the programming languages we, as a directive-based parallel programming model, support, namely C, C++, and Fortran. When we released OpenACC 1.0 in November of 2011 the most important programming languages in scientific and high performance computing were C99, C++98, and Fortran 2003.