Academics vs. Engineers: PyPy vs. V8
It's interesting to see how academics attack a problem and how engineers do it. In this post I'll take a look at the two approaches.
The two fighters
In the red ring corner you have PyPy - an implementation of Python in Python itself. The project is ambitious and at some points obscure (for example, they dig into Prolog to get some experience with JIT compilation).
PyPy has been underway for a long time (around 6 years) without producing anything that can be used in production. Their goal is quite ambitious and their ways of exploring the space is at some places innovative and uncommon. Their end-goal is to produce a fully compatible Python implementation. So far they don't have a fully compatible Python, but only a subset.
It's two very different ways of attacking a problem. The academics attack it to gain new insights, while engineers attack the problem to solve it using currently available knowledge. It should be noted thought that engineers might also gain new insights while solving a problem, Lars Bak has for example 18 patents in VM technology.