In comp.lang.fortran E.D.G. <edgrs...@ix.netcom.com> wrote: >>> "E.D.G." <edgrs...@ix.netcom.com> wrote in message >>> news:ro-dnch2dptbrhnpnz2dnuvz_rsdn...@earthlink.com... > Posted by E.D.G. on November 19, 2013 > 1. PERL PDL CALCULATION SPEED VERSUS PYTHON AND FORTRAN (snip)
> This program translation project has become one of the most > surprisingly successful programming projects I have worked on to date. A > considerable amount of valuable information has been sent to me by E-mail in > addition to all of the information posted to the Newsgroups. > The original posts actually discussed calculation speed matters > involving Perl and Python. And responses indicated that there were ways to > develop routines that could dramatically accelerate Python calculations. > But it did not sound like there were any for Perl. In general, language processors can be divided into two categories called compilers and interpreters. Compilers generate instructions for the target processors. Interpreters generate (usually) an intermediate representation which is then interpreted by a program to perform the desired operations. That latter tends to be much slower, but more portable. There are a few langauges that allow dynamic generation of code, which often makes compilation impossible, and those languages tend to be called 'interpreted langauges'. Some years ago when working with perl programs that ran too slow, we found a perl to C translator. Surprisingly, the result ran just as slow! It turns out that the perl to C translator generates a C program containing the intermediate code and the interpreter, and so runs just the same speed. More recently, there are JIT systems which generate the intermediate code, but then at the appropriate time (Just In Time) compile that to machine code and execute it. This is common for Java, and more recently for languages like Matlab. -- glen -- https://mail.python.org/mailman/listinfo/python-list
