Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!sdd.hp.com!spool.mu.edu!cs.umn.edu!ariel.unm.edu!triton.unm.edu!prentice From: prentice@triton.unm.edu (John Prentice) Newsgroups: comp.lang.fortran Subject: Re: Fortran 90 status Message-ID: <1991Apr27.054003.22792@ariel.unm.edu> Date: 27 Apr 91 05:40:03 GMT References: <123207.25873@timbuk.cray.com> <1991Apr26.210247.17264@ariel.unm.edu> <1991Apr27.013231.27187@convex.com> Organization: University of New Mexico, Albuquerque, NM Lines: 38 In article <1991Apr27.013231.27187@convex.com> psmith@convex.com (Presley Smith) writes: > >So, if you want parallelism in the near term, you'll have to look >somewhere else... Fortran 90 does not solve that problem. > Yep, precisely my point. Now, given that Fortran is regarded mostly, if not exclusively, as a scientific language and given that parallelism is rapidly becomeing standard for scientific computing, where does that leave Fortran? If it fails to address the needs of the scientific community, it will get left behind. I am not trying to trash the development of standards here, but I am pointing out that the process may very well destroy the language, particularly if standards take 14 years to even agree on and another 8 or 9 to implement. I don't know what the solution is, but I am pretty confident that the system is totally out of whack as it stands. It is interesting to me that many, if not most, people I know in computing complain about how the IBM PC terribly retarded the micro industry by locking into a poor technology. I know others who complain bitterly about UNIX because it is a very old operating system. Yet we enshrine the concept of going slow and knowingly retarding the technology with language standards. There are good arguments for all this, but they implicitly are based on the idea that things will not change too rapidly. But the computer industry IS changing very rapidly and I quite expect that very few of the old standby languages like Fortran and C are going to be serious players in the future, just because they are inherently too slow to accommodate the changing needs of the community. My conclusion? Like it or not, get used to learning and adapting to new languages until such time, if ever, things stabilize again. I don't like that conclusion, but I don't see any alternatives for scientists trying to stay on the leading edge of computing. John -- John K. Prentice john@unmfys.unm.edu (Internet) Dept. of Physics and Astronomy, University of New Mexico, Albuquerque, NM, USA Computational Physics Group, Amparo Corporation, Albuquerque, NM, USA