Where does Julia (ecosystem) provide the greatest speedup, and where does it lag the most behind (compared to e.g. Python)?

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When I talk about Julia, I talk about three levels of performance improvements:

  1. Avoiding traditional dynamic language overheads. (see Why Are Languages Like Python and MATLAB So Much Slower than Julia? - #9 by mbauman)
  2. Implementing better algorithms. Using a productive high-level language that is also fast (see point 1) can enable rapid development of new and smarter algorithms.
  3. Exploiting parallelism and accelerators like GPUs.

These speedups are, of course, multiplicative. The ecosystems that see the greatest speedups will be those that are still stuck on step 1. Differential Equations and CSV reading are both good examples of areas where step 1 has been “solved” in most languages, but Julia’s ecosystem is head and shoulders above in steps 2 and 3.

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