From mboxrd@z Thu Jan 1 00:00:00 1970 X-Spam-Checker-Version: SpamAssassin 3.4.4 (2020-01-24) on polar.synack.me X-Spam-Level: X-Spam-Status: No, score=-1.3 required=5.0 tests=BAYES_00,INVALID_MSGID autolearn=no autolearn_force=no version=3.4.4 X-Google-Language: ENGLISH,ASCII-7-bit X-Google-Thread: 103376,42b96374c851ce5a X-Google-Attributes: gid103376,public From: Gautier Subject: Re: Ada for numerics computation (i.e. forget Fortran ?) Date: 1999/04/23 Message-ID: <37209E8F.4D4D3989@Maths.UniNe.CH>#1/1 X-Deja-AN: 470033371 Content-Transfer-Encoding: 7bit References: <372083A1.45A5EB97@t-online.de> To: "Hans N. Beck" Content-Type: text/plain; charset=us-ascii MIME-Version: 1.0 Newsgroups: comp.lang.ada Date: 1999-04-23T00:00:00+00:00 List-Id: > does anyone has experiences with Ada and numerical > applications ? Yes, me ;-) > Does Ada fit for this ? Yes. > It's not only a question of types > available, but also > of efficiency (speed) of the compilers. Yeeeees I know, in > the most cases Fortran > is used, but perhaps anyone walks on new fields ? * Speed: same between DEC Fortran & DEC Ada, Lahey Fortran and GNAT/DOS for simple things. (pragma suppress_all -> =Fortran; else -> slower for debugging). For big programs Ada is faster with a smart usage of cross-package inlining (available with GNAT) and subtyping. * Coding time, debugging time, human energy: you _can_ forget Fortran! There are plenty of numerics resources there: http://amok.ast.univie.ac.at/~stift/stift_home.html For finite elements, sparse matrices, etc. contact me for some sources. -- Gautier -------- http://members.xoom.com/gdemont/