🚀 go-pugleaf

Preston Briggs writes:
;> I'm still hoping to see somebody recode matrix multiply in C, using 
;> all the source hacks they want, so we can compare it to what we get
;> using Fortran and our (not mine, friends') latest transformations.
;> . . .

While we're on the topics of recoding, and how well source code maps
onto a machine, why not consider a few other mainstream languages
besides C and Fortran??????

I mean, C++ seems to rectify a large number of the problems one sees
with C.  (It allows inline functions, for example.)  You still have
pointers, but g++ (gnu's C++) allows one to declare that a function
has no side effects, allowing the optimizer to fold calls to it.  (gcc
has both of these features too, and for "hello world" programs
generates smaller code, but I'm getting tired of only hearing about c
vs FORTRAN.) 

On the other hand, there are languages like APL which with a few
changes (like variable scoping, and function rank declaration) ought
to make very nice compiling languages.  /* APL implementation of
matrix multiply:  A <- B +.x C */.  From what I've heard, it is
possible to DEVELOP code in APL about 6 or 7 times faster than what is
usual with FORTRAN.  (Weren't the two big advantages of FORTRAN over c
supposed to be that FORTRAN is faster to write, and FORTRAN allows
more optimizations in compilation, especially as machine architectures
change???)

--
Raul Rockwell
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