Simply fortran cuda support software#

However, a cynical (or visionary – it’s only a matter of perspective) observer might suggest that the best ideas of these will be (eventually) absorbed into mainstream options – either directly into the Fortran or C languages, or through community add-ons, or through the parallel programming models. There are several of these created with HPC in mind from the start – such as Chapel (supported by Cray) and X10 (supported by IBM), both of which support abstractions designed to simplify programming at scale. That is not to diminish the value of new and clever languages. There are, of course, a surplus of options for both. The first is the programming language(s) to use, and the second is the choice of parallel programming model(s). If we cut it down to its simplest form, there are two choices to make when programming for HPC.

Simply fortran cuda support software#

When planning the development or enhancement of application software to use HPC facilities, or planning for future HPC system options, one of the most important technology questions is the programming technology options.

However, many of us still easily have our attention grabbed by the hardware – future processors, new architectures, esoteric options such as quantum computing – leaving the needs of programming, user interfaces, skills development, careers and diversity hiding at the back of the room. We proudly, and rightly, advocate that the ability of HPC to deliver results to science, engineering and business and this relies not just on hardware but also on software and people. There is a gentle touch of hypocrisy about the supercomputing world.