The coarray programming model is an expression of the Single-Program-Multiple-Data (SPMD) programming model through the simple device of adding a codimension to the Fortran language. A data object declared with a codimension is a coarray object. Codimensions express the idea that some objects are located in local memory while others are located in remote memory. Coarray syntax obeys most of the same rules for normal array syntax. It is familiar to the Fortran programmer so the use of coarray syntax is natural and intuitive. Although the basic idea is quite simple, inserting it into the language definition turned out to be difficult. In addition, the process was complicated by rapidly changing hardware and heated arguments over whether parallelism should be supported best as an interface to language-independent libraries, as a set of directives superimposed on languages, or as a set of specific extensions to existing languages. In this paper, we review both the early history of coarrays and also their development into a part of Fortran 2008 and eventually into a larger part of Fortran 2018. Coarrays have been used, for example, in weather forecasting and in neural networks and deep learning.

We present novel parallel language constructs for the communication intensive part of a magnetic fusion simulation code. The focus of this work is the shift phase of charged particles of a tokamak simulation code in toroidal geometry. We introduce new hybrid PGAS/OpenMP implementations of highly optimized hybrid MPI/OpenMP based communication kernels. The hybrid PGAS implementations use an extension of standard hybrid programming techniques, enabling the distribution of high communication work loads of the underlying kernel among OpenMP threads. Building upon lightweight one-sided CAF (Fortran 2008) communication techniques, we also show the benefits of spreading out the communication over a longer period of time, resulting in a reduction of bandwidth requirements and a more sustained communication and computation overlap. Experiments on up to 130560 processors are conducted on the NERSC Hopper system, which is currently the largest HPC platform with hardware support for one-sided communication and show performance improvements of 52 % at highest concurrency.