Isn't there a lot of daylight between old Fortran code and AI?
What if we rewrote the old algorithms in C with modern techniques? Multitthreading? Or GPU compute? If there's value there, I could do these things. Probably wouldn't take that long
What if we rewrote the old algorithms in C with modern techniques? Multitthreading? Or GPU compute? If there's value there, I could do these things. Probably wouldn't take that long
Fortran compilers had more than 40 years to become pretty good at generating efficient code; they can make assumptions that are not possible in C (for example, no aliasing) to do so. Besides, most compilers already can do vectorization and autoparallelisation with multithreading, coarrays, and/or openMP, which can be offloaded to a GPU.
Then it's not done yet.
Plus, even after doing that, there would still be a sim2real gap. The goal of our research is to use physics informed deep learning and methods with strong inductive biases, combined with transfer learning and low-shot learning to overcome the sim2real gap.