Single threaded, NumPy offers basically the same syntax and speed as Fortran when it comes to vector operations. Therefore, the slides boil down to "CoArrays be

Single threaded, NumPy offers basically the same syntax and speed as Fortran when it comes to vector operations. Therefore, the slides boil down to "CoArrays being the Fortran killer application". I don't feel this is the whole truth. You can (and many people do) write a modern Fortran MPI-CoArray application for HPC and it can be slim, compile and run fast. No big ecosystem, like a small C application. The same is most likely not true if you include Python in your toolchain and then use some FFI to call C or Fortran in performance critical sections. As the author, you might be able to hide the ugliness (such as Numpy does it), but it can be a show stopper for maintainability and future generations working with the code. That's probably why still so many new HPC codes are pure Fortran/C codebases and Julia or Python remains the language for postprocessing data on workstations.