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=-1.9 required=5.0 tests=BAYES_00 autolearn=ham autolearn_force=no version=3.4.4 X-Google-Thread: 103376,c4cb2c432feebd9d X-Google-Thread: 1094ba,c4cb2c432feebd9d X-Google-Attributes: gid103376,gid1094ba,public X-Google-Language: ENGLISH,ASCII-7-bit Path: g2news2.google.com!news4.google.com!news3.google.com!news2.volia.net!news.germany.com!newsfeed3.funet.fi!newsfeeds.funet.fi!nntp.hut.fi!not-for-mail From: Janne Blomqvist Newsgroups: comp.lang.ada,comp.lang.fortran Subject: Re: Ada vs Fortran for scientific applications Followup-To: comp.lang.fortran Date: Thu, 25 May 2006 22:43:08 +0300 (EEST) Organization: Helsinki University of Technology Message-ID: References: <44734543.80609@cits1.stanford.edu> NNTP-Posting-Host: vipunen.hut.fi X-Trace: epityr.hut.fi 1148586188 26126 130.233.228.9 (25 May 2006 19:43:08 GMT) X-Complaints-To: usenet@hut.fi NNTP-Posting-Date: Thu, 25 May 2006 19:43:08 +0000 (UTC) User-Agent: slrn/0.9.7.2 (SunOS) Xref: g2news2.google.com comp.lang.ada:4469 comp.lang.fortran:10253 Date: 2006-05-25T22:43:08+03:00 List-Id: In article , Rich Townsend wrote: > Brooks Moses wrote: >> Rich Townsend wrote: >>> My stance on A*B is this: if A*B denotes matrix multiplication, then >>> A/B should denote matrix 'division': B^-1*A. Which means you need to >>> standardize matrix inversion/linear-equations solution into the >>> language. Which is batshit crazy. >> >> >> I believe that's how Matlab does it. >> >> Then again, for Matlab's purposes, standardizing matrix inversion and >> linear-equation solution into the language is entirely reasonable. >> > > Exactly. But I don't think you would find a single person in this newsgroup who > would support inclusion of a solver in Fortran. And the reason would be netlib. Well, if a solver were included in the standard or more to the point in the One True Compiler (TM), then perhaps we wouldn't need these ridiculous "fastest matrix inversion" contests. -- Janne Blomqvist