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Computing Facilities for AI AI Magazine Volume 2 Number 1 (1981) (© AAAI) Computino Facilities A Survey of Present and Near-Future Options Scott Fahlman Department of Computer Science Carnegie-Mellon University Pittsburgh, Pennsylvania 15213 At the recent AAAI conference at Stanford, it became isolate the research group from the rest of the AI apparent that many new AI research centers are being community. It seems a much wiser course to tie one’s established around the country in industrial and center in with others, so that tools and results can be governmental settings and in universities that have not shared paid much attention to Al in the past. At the same time, many of the established AI centers are in the process of Of course, this does not mean that one cannot do AI converting from older facilities, primarily based on research on practically any machine if there is no other Decsystem-IO and Decsystem-20 machines, to a variety of choice. Good AI research has been done on machines newer options. At present, unfortunately, there is no from Univac, Burroughs, Honeywell, and even IBM, using simple answer to the question of what machines, operating unbelievably hostile operating systems, and in languages systems, and languages a new or upgrading AI facility ranging from Basic to PL-I. If corporate policy or lack of should use, and this situation has led to a great deal of independent funds forces some such choice on you, it is confusion and anxiety on the part of those researchers and not the end of the world. It should be noted, however, administrators who are faced with making this choice. In that the lack of first-rate facilities is very likely to lead to a this article I will survey the major alternatives available at lack of first-rate people, and will have a serious impact on present and those that are clearly visible on the horizon, the productivity of the people you do manage to attract. and I will try to indicate the advantages and disadvantages In this article, then, I will concentrate on the choices that of each for AI work. This is mostly information that we might be made by centers that have a free choice in the have gathered at CMU in the course of planning for our matter and the funds to obtain facilities that will be own future computing needs, but the opinions expressed dedicated to AI use. are my own. One other warning must be given: this material will Before going on, 1 should note this discussion will be become obsolete very quickly. If you should encounter limited to those machines and systems that are (or will be) this article a year after publication, much of it will be out in active use at one or more of the major established of date. If the time is two years after publication, it will be centers of AI research in the United States. This totally worthless. limitation is deliberate. in my opinion, it would be unwise for a new center to start from scratch with a machine or system that has not previously been used for serious AI Basic Computing Needs research. To do so would be to take on a tool-building task that would delay the beginning of serious AI research What does an AI researcher want from his computing for several years. Using an odd machine also tends to facility? What will make him most productive? Setting 16 Al MAGAZINE Winter 1980-81 aside, for now, the very specialized needs of those doing another via computer mail. First-rate facilities signal processing or robotics, the needs of the rest are for all these activities must be provided. My relatively straightforward to state, if difficult to satisfy. In own working definition of “first-rate”, among fact, the needs of the Al researcher are not very different systems available today, would be the from the needs of any other researcher in computer combination of Emacs and Scribe. Tastes may science, except that facility-related problems seem to vary in this, but it is clear that the use of a become acute in AI a few years sooner than they are felt teletype-oriented editor or a primitive in other research areas The considerations are roughly as text-processing system can waste a great deal follows: of your researchers’ valuable time 0 AI programs tend to be very large because they 0 The programming done in AI is almost always contain, in one form or another, a lot of of an experimental, evolutionary nature, and it knowledge. It follows, then, that any machine is concerned mostly with symbol manipulation used for AI must provide a large virtual rather than arithmetic This argues very address space in order to insulate the strongly for the use of Lisp over other researcher from having to think about how to currently-available languages An AI research chop up his task into smaller tidbits and center must provide a well-developed, overlays. A 32-bit address space is comfortable well-maintained Lisp system; other languages for the forseeable future; a 24-bit (to the 32-bit are optional. The use of such languages as Sail word) address space is adequate for the next for AI research seems to be declining rapidly couple of years for most purposes; the 1%bit now that good Lisps are widely available It address space of the Dee-lo/20 series is may be, as some researchers argue, that woefully inadequate and has seriously impeded Smalltalk-like languages are the wave of the the recent progress of Al. Don’t even think future, but that wave is still well over the about using anything smaller. horizon for most of us. 0 Most AI programs burn a lot of cycles. If your As 1 said, these requirements are simple to state, but machine is slow or is too heavily loaded, your hard and expensive to realize. To equip an AI center in a high-powered researchers will be spending all way that will help you to attract the best people, you of their time waiting for something to happen should probably plan to spend something like $50K-$70K on their screens They will spend this time per researcher in computing equipment. (For serious work plotting against the management and reading in robotics, plan to spend a lot more > An established the help-wanted ads To pack too many center can get by with less, but if you are trying to start a researchers onto a time-shared machine is a new center it will be very hard to recruit people to work move of very dubious economic value. with inferior facilities There are many examples of q The operating system must be friendly. For well-intentioned efforts that never reached critical mass in AI, friendliness means flexibility Protection people because the computing environment was wrong. and quotas must not get in the way, the In providing these facilities, there are two basic utilities must be screen-oriented rather than paper-oriented, documentation must be on-line approaches: time-sharing and the use of powerful personal machines connected by a high-bandwidth network. and easy to use, and individ’ual users must have easy access to multiple processes so that Time-sharing has been the mainstay of the field for over a some of the waiting time can be spent editing decade and, as I write this, is still the only option available or doing other useful work. Most important, from commercial sources. The personal computing option the system should stay up: when you have is expected by most leaders in the field to be the dominant invested an hour of CPU time and eight hours force of the next decade, starting very soon, but it will be of your own time in a computation, a crash can a year or two before it is a practical option for users who be very irritating. Since most AI researchers do not want to do a lot of the development themselves are experienced programmers, a user interface That is one of the reasons why the field is currently so that is easy for beginners to use is relatively unsettled: users must acquire enough time-sharing capacity less important than on a machine for general to meet their present needs, but they want to save enough use, but remember that you may want to equipment money to allow for a quick move into the export your results to an environment with less personal-computing world as soon as this becomes sophisticated users. practical. We will consider the options in both of these worlds in the following sections. 0 Though AI researchers spend more of their time computing than most people in computer science, they still spend most of their time Time-Sharing Options editing programs, editing text, formatting documents, and communicating with one Two families of time-sharing machines are used by the Al MAGAZINE Winter 1980-81 17 vast majority of AI researchers: the Decsystem-20 (and its family relatively unattractive. An option that some users predecessor, the Decsystem-lo), and the Vax, both may want to consider is a line of machines from Foonly, products of the Digital Equipment Corporation. As I said Incorporated These machines execute the Dee-20 earlier, it is possible to do AI on other machines, but instruction set and can therefore run most of the same anyone with a choice in the matter should probably stick software They tend to be substantially less expensive with these two hardware families. than the comparable machines from DEC, but they must run Tenex rather than Tops-20, and maintenance may be a problem in some areas.
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