Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP Posting-Version: Notesfiles $Revision: 1.7.0.10 $; site uiucdcsp Path: utzoo!watmath!clyde!cbosgd!ihnp4!inuxc!pur-ee!uiucdcsp!forbus From: forbus@uiucdcsp.CS.UIUC.EDU Newsgroups: net.ai Subject: Re: Workstations vs Timeshare Message-ID: <3500009@uiucdcsp> Date: Sat, 9-Nov-85 09:24:00 EST Article-I.D.: uiucdcsp.3500009 Posted: Sat Nov 9 09:24:00 1985 Date-Received: Mon, 11-Nov-85 06:19:15 EST References: <3528@utah-cs.UUCP> Lines: 39 Nf-ID: #R:utah-cs.UUCP:3528:uiucdcsp:3500009:000:2368 Nf-From: uiucdcsp.CS.UIUC.EDU!forbus Nov 9 08:24:00 1985 1. Time sharing systems are in trouble if TWO people are actually hacking. Assuming that only one person in a community at a time is either debugging or experimenting with an AI program at a time is assuming that that community isn't really doing much research. Implying that using a computer more than that is just "hacking without thinking" (to paraphrase) does a grave injustice to the experimental side of AI. Far too often programs have been run on only one example, if that, and part of the reason has been lack of cycles. Technology is fixing this situation, but not fast enough for my taste. The more time I and my students spend shoehorning our programs onto processors that are too small (or too overcrowded), the less time we are thinking about AI. Consequently, I try to get my students the best sources of cycles that money can buy (modulo the fact that no funding agency will buy us several CRAY's to use as single-person workstations, and we couldn't physically house them as well. But then again, with two supercomputer centers on campus....). We STILL have to shoehorn, but it takes a much smaller fraction of our time than people who are struggling along on Apollos or Suns. 2. 8MB of memory sure will run faster than 4MB! (If only someone would second-source boards for Symbolics machines I'd upgrade all of ours accordingly.) However, how many people can afford 100-200MB of real memory right now? I've seen programs eat up that much quite often (not just mine!). Look, if you want to make a program that knows alot (or does some deep analysis of something), then you have to put that knowledge somewhere. 8MB total address space may be fine for small applications programs, but not for serious research. Until memory gets VERY cheap, paging will be with us. I think it's all pretty clear: Say a vax 780 is 500K. A reasonable 3640 configuration is around 80K list (and if you are a university you can do much, much better). For 500K you can get 6 3640's at list price (and at university discount a few extra on top of that), each of which will outperform a stand-alone 780 running Common Lisp, not to mention a 780 struggling along with 6 CL users....right now, the technology and marketplace make workstations the only sensible choice for serious AI research. Tomorrow might be different, but that's how it seems to be today.