Hello, On Friday, June 6, 2014 3:02:43 PM UTC+2, Reid Atcheson wrote: > > An important thing to factor in here as well is developer time. With Julia > you can arrive at a prototype functional code in far less developer time > than with C/Fortran. From there you can iterate on the code once you have > identified the performance critical components. As a last step if the code > still isn't fast enough you can write your own external C or Fortran code > and use "ccall" just for those spots which cost the most, and you have the > additional benefit also of having existing functional code to test against > to see that everything still checks out. > > In addition, while doing all this you have access to a full set of very > useful tools that help to see under the hood of numerical algorithms, like > eigenvalue or SVD calculations. You can easily interact with the data that > julia is processing by playing with it in the REPL. >
You explain the situation for python/numpy or Matlab users. In julia you can go down from a high-level language to a low-level language without leaving the environment, That's the USP (at the moment).
