On 2007-12-10, sturlamolden wrote: > We have seen several examples that 'dynamic' and 'interpreted' > languages can be quite efficient: There is an implementation of Common > Lisp - CMUCL - that can compete with Fortran in efficiency for > numerical computing. There are also versions of Lisp than can compete > with the latest versions of JIT-compiled Java, e.g. SBCL and Allegro. > As it happens, SBCL and CMUCL is mostly implemented in Lisp. The issue > of speed for a language like Python has a lot to do with the quality > of the implementation. What really makes CMUCL shine is the compiler > that emits efficient native code on the fly. If it is possible to make > a very fast Lisp, it should be possible to make a very fast Python as > well. I remember people complaining 10 years ago that 'Lisp is so > slow'. A huge effort has been put into making Lisp efficient enough > for AI. I hope Python some day will gain a little from that effort as > well.
I've been told that Torbjörn Lager's implementation of the Brill tagger in Prolog is remarkably fast, but that it uses some counter-intuitive arrangements of the predicate and argument structures in order to take advantage of the way Prolog databases are indexed. -- http://mail.python.org/mailman/listinfo/python-list
