Re:Julia Computing Raises $4.6M in Seed Funding
by ferdterguson on Tuesday June 20, 2017 @10:27PM
(#14600219)
> Python in some cases can be 100x slower than C
Yeah, the Python implemented version is. But people doing serious computing in Python that requires speed are doing it with NumPy or even Cython or just straight up calling C/Fortran libraries in Python.
Performance, assuming identical hardware, depends on the program itself (that is, on what you are trying to calculate or compute or perform), but if you choose many different programs you can have a comparison between platforms ("platform" in this case means combination of programming language plus compiler or interpreter.)
Here is a graphic comparing Julia to other platforms: https://julialang.org/benchmarks/
You can see that according to that graphic, R can be up to 400x slower than Julia (or C).
There is another independent benchmark here. It does not include R but it includes Python, and it's very interesting.
http://benchmarksgame.alioth.debian.org/
But the best comparison graphs are here, this is worth a look: http://blog.gmarceau.qc.ca/2009/05/speed-size-and-dependabil...