Skip to main content
Software Engineering

You are not logged in. Your edit will be placed in a queue until it is peer reviewed.

We welcome edits that make the post easier to understand and more valuable for readers. Because community members review edits, please try to make the post substantially better than how you found it, for example, by fixing grammar or adding additional resources and hyperlinks.

Required fields*

12
  • 3
    Money. The money that used to be poured into C++ and Fortran now is poured into the HotSpot, CLR, Mono, V8, Nitro, SpiderMonkey, etc. Commented Sep 30, 2013 at 23:54
  • I can only guess, but I think it is just improvement over time, like described here joelonsoftware.com/articles/fog0000000017.html Commented Oct 1, 2013 at 6:01
  • 1
    RE how PyPy can be faster than CPython: It isn't written in Python, it's written in a quite different language that can be AOT-optimized effectively. Commented Oct 1, 2013 at 10:08
  • 1
    @Gomi It's not about how similar the implementation language is to the implemented language. There are JavaScript, Lisp, Prolog, SmallTalk and Ruby interpreters written in RPython and they get exactly the same goodies PyPy offers. The only reason RPython is based on Python is that it was created by a bunch of Python enthusiasts. The features of RPython that make PyPy fast have nothing to do with Python: Automatic JIT compiler generation, the garbage collectors, etc. - and yes, most of that could in principle be done using other languages. You'd have to create a whole new compiler though. Commented Oct 1, 2013 at 15:29
  • 4
    -1 because you seem to have at least 3 different questions here: (a) Why are meta-circular implementations so good? (b) Are VMs efficient because of type information, and is introspection beneficial for performance? (c) How come VM popularity surged in the late 2000s, and how come they all of a sudden have good performance? I think it's better to ask those questions separately. Commented Oct 2, 2013 at 6:39