a system's performance under extreme conditions. Finally, it is often difficult to show that a simulation is valid that is, that it actually does simulate the system in question." (Huesmann and Goldberg, 1967, p. 150). 7.21 "The field of information retrieval has been marked by a paucity of mathematical models, and the basis of present operational computer retrieval systems is essentially heuristic in design." (Baker, 1965, p. 150). "The semantic and linguistic aspects of information retrieval systems also lend themselves poorly to the rigidity of models and model techniques, for which claims often lack empirical support." (Blunt, 1965, p. 105). 7.22 "There are structures which can easily be defined but which present-day mathematics cannot handle because of the limitations of presentday theory." (Hayes, 1963, p. 284). "Markov models cannot, in general, be used to represent processes where other than random queuing is used." (Scherr, 1965, p. 32). "Clearly, we need some mathematical models permitting the derivation of methods which will accomplish the desired results and for which criteria of effectiveness can be determined. Such models do not appear often in the literature." (Bryant, 1964, p. 504). "First, it will be necessary to construct mathematical models of systems in which content, structure, communication, and decision variables all appear. For example, several cost variables are usually included in a typical operations research model. These are either taken as uncontrollable or as controllable only by manipulating such other variables as quantity purchased or produced, time of purchase or production, number and type of facilities, and allocation of jobs to these facilities. These costs, however, are always dependent on human performance, but the relevant variables dealing with personnel, structure, and communication seldom appear in such models. To a large extent this is due to the lack of operational definitions of many of these variables and, consequently, to the absence of suitable measures in terms of which they can be characterized." (Ackoff, 1961, p. 38). "Mathematical analysis of complex systems is very often impossible; experimentation with actual or pilot systems is costly and time consuming, and the relevant variables are not always subject to control. . . . "Simulation problems are characterized by being mathematically intractable and having resisted solution by analytic methods. The problems usually involve many variables, many parameters, functions which are not well-behaved mathematically, and random variables. Thus, simulation is a technique of last resort." (Teichroew and Lubin, 1966, p. 724). "The complex systems generally encountered in the real world do not lend themselves to neat mathematical formulations and in most cases the operations analyst is forced to reduce the problem to simpler terms to make it tractable." (Clapp, 1967, p. 5). "Admittedly the degree to which identifiable factors can be measured-compared to the influence of unidentifiable factors - does help determine whether or not an approach can be scientific. It acts as a limit on the area where scientfic methods can be applied. Precision in model building is relating to the difficulty of the problem and the state of human knowledge concerning specific techniques and their application." (Kozmetsky and Kircher, 1956, p. 137). 7.23 "There is no guarantee that a model such as latent class analysis, factor analysis, or anything else borrowed from another field will meet the needs of its new context; however this should not dissuade one from investigating such plausible models." (Baker, 1965, p. 150). "Models must be used but must never be believed. As T. C. Chamberlain said, 'science is the holding of multiple working hypotheses'." (Tukey and Wilk, 1966, p. 697). 7.24 "System simulation or modeling was subsequently proposed as a substitute for deriving test problems and is still generally accepted as such even though its use introduced the new difficulty of determining and building meaningful models." (Davis, 1965, p. 82). "The biggest problem in simulation modeling, as in all model building, is to retain all 'essential' detail and remove the nonessential features." (Scherr, 1965, p. 109). "The fundamental problem in simulation of digital networks is that of economically constructing a mathematical model capable of faithfully replicating the real network's behavior in regard to simulation objectives." (Larsen and Mano, 1965, p. 308). 7.25 "At this time, there exists no specialpurpose simulation programming language specifically for use with models of digital computer systems. The general-purposes languages, such as SIMSCRIPT, GPSS, etc., all have faults which render them unsuitable for this type of work." (Scherr, 1965, p. 43). "The invention of an adequate simulation language promises to be the crowbar needed to bring the programming of operating systems to the level of sophistication of algebraic or commercial programming languages." (Perlis, 1965, p. 192). "The technique of input simulation . . . can be very expensive. The programs necessary to create the simulated inputs are far from trivial and may well constitute a second system larger than the operational system." (Steel, 1965, p. 232). 7.26 "Those programs which require the simulated computer system and job mix to be specified in algebraic or assembly languages have proved useful; but as general computer systems simulation tools, they require too much difficult recording to be completely satisfactory. One way to improve upon this situation has been to use languages specifically designed to simulate systems. Teichroew and Lubin in a recent review have listed more than twenty languages, among them GPSS, SIMSCRIPT, SOL, and CSL. These simulation languages allow the modeller to specify the computer configuration and job mix in a more convenient manner. (Huesmann, and Goldberg, 1967, p. 152). 7.27 "One of the more exotic applications of digital computers is to simulate a digital computer on another entirely different type of computer. Using a simulation program, application programs developed for the first computer, the source computer, may be executed on a second computer, the object computer. "Simulation obviously provides many advantages in situations where a computer is replaced by a different computer, for which the applications have not yet been programmed. Simulation techniques enable an installation to continue solving problems using existing programs after the new computer has been installed and the old one removed. . . "Another situation in which simulation is advantageous is during the development of a new computer. Once specifications for the new computer have been established, programming of applications for the computer can proceed in parallel with hardware developments. The use of a simulator in this situation enables the users to debug their applications before the hardware is actually available." (Trimble, 1965, p. 18). "One of the most successful applications of the recent microprogramming technology is in the simulation of computers on computers. "The microprogram control and the set of microprogram routines are in effect a simulation program that simulates the programmer's instruction set on a computer whose instruction set is the set of elementary operations. It may be equally possible to simulate computers with other programmer instruction sets in terms of the same set of elementary operations. This, slightly oversimplified perhaps, is the idea of hardware assisted simulation that is now usually called emulation." (Rosen, 1968, p. 1444). "As a result of simulation's ability to deal with many details, it is a good tool for studying extensive and complicated computer systems. With simulation, one may assess the interaction of several subsystems, the performances of which are modified by internal feedback loops among the subsystems. For instance, in a teleprocessing system where programs are being read from drum storage and held temporarily in main storage, the number of messages in the processing unit depends upon the drum. response time, which depends upon the drum access rate, which, in turn, depends upon the number of messages in main storage. In this case, only a system-wide simulation that includes communication lines, processing unit, and I/O subsystems will determine the impact of varying program priorities. on main-storage usage. Studies of this nature can become very time consuming unless parameter selections and variations are carefully limited. It is no small problem to determine which are the major variations that affect the system. In this aspect, simulation is not as convenient as algorithmic methods with which many variations can be tabulated quickly and cheaply." (Seaman, 1966, p. 177). 7.28 "The [SIMSCRIPT] notation is an augmented version of FORTRAN, which is acceptable; but this organization does not take advantage of the modularity of digital systems. "SIMSCRIPT is an event-based language. That is, the simulation is described, event by event, with small programs, one per event. Each event program (or sub-program) must specify the times for the events following it. Conditional scheduling of an event is extremely difficult." (Scherr, 1965, p. 43). 7.29 Ewards points out that ". . . the preparation of so-called scenarios, or sequences of events to occur as inputs to the simulation, is a major problem, perhaps the most important one, in the design of simulations, especially simulations of information-processing systems." (Edwards, 1965, p. 152). 7.30 "Parallel processes can be rendered sequential, for simulation purpose; difficulties then arise when the processes influence each other, leading perhaps to incompatibilities barring a simultaneous development. Difficulties of this type cannot be avoided, as a matter of principle, and the system is thus not deterministic; the only way out would be to restore determinism through recourse to appropriate priority rules. This approach is justified only if it reflects priorities actually inherent in the system." (Caracciolo di Forino, 1965, p. 18). 7.31 "As a programming language, apart from simulation, SIMULA has extensive list processing facilities and introduces an extended co-routine concept in a high-level language." (Dahl and Nygaard, 1966, p. 671). 7.32 "The LOMUSS model of the Lockheed UNIVAC on-line, time-sharing, remote terminal system simulated two critical periods . . . and provided information upon which the design of the 1108 system configuration was based. An effort is continuing which will monitor the level and characteristics of the workload, equipment utilization, turnaround time, etc., for further model validation." (Hutchinson and Maguire, 1965, pp. 166–167). "A digital computer is being used to simulate the logic, determine parts values, compute subunit loading, write wiring lists, design logic boards, print checkout charts and maintenance charts. Simulating the logic and computing the loading of subunits gives assurance that a computer design will function properly before the fabrication starts. After the logic equations are simulated, it is a matter of hours until all fabrication information and checkout information is available. Examples are given of the use of these techniques on the design and fabrication of a large scale military computer." (Malbrain, 1959, p. 4-1). "The new EDP Machine Logic and Control Simulator, LOCS, is designed to facilitate the simulation of data processing systems and logic on the IBM 7090 Data Processing System. . . The inputs of LOCS consist of a description of the machine to be simulated, coded in LOCS language, and a set of test programs coded in either the procedure language of the test problems (e.g., FORTRAN) or in the instruction language of the simulated machine . . . The outputs of LOCS consist of the performance statistics, computation results, and diagnostic data which are relevant to both the test programs and the design of the simulated machine.” (Zucker, 1965, pp. 403-404). 66 7.33 ". . . A system of software and hardware which simulates, with a few exceptions, a multiple set of IBM System/360 computing systems (hardware and software) that are simultaneously available to many users." (Lindquist et al., 1966, p. 1775). 7.34 "Another simulation program designed to simulate multiprocessor systems is being developed by R. Goldstein at Lawrence Radiation Laboratory. Written in SIMTRAN, this program is specifically designed to simulate the OCTOPUS computer system at LRL which includes an IBM 7030 STRETCH, two IBM 7094's, two CDC 6600's, one CDC 3600, two PDP 6's, an IBM 1401, and various I/O devices. A parameterized input table specifies the general multiprocessing configuration, the data transmission rates, memory sizes and buffer sizes. Any other hardware variations and operating system characteristics are introduced with SIMTRAN routines. As output the program produces figures on actual memory utilization, graphs of memory access time, graphs of overhead, graphs of response time, and graphs of several other relevant variables." (Huesmann and Goldberg, 1967, p. 153). 7.35 "One of the more exotic applications of digital computers is to simulate a digital computer on another entirely different type of computer. Using a simulation program, application programs developed for the first computer, the source computer, may be executed on a second computer, the object computer." (Trimble, 1965, p. 18). 7.36 "The flexibility of a digital computer enables one to try out complicated picture processing schemes with a relatively small amount of effort. To facilitate this simulation, a digital picture scanner and cathode-ray tube display was constructed. Pictures were scanned with this system, the signal was recorded on a computer magnetic tape, and this tape was used as input to a program that simulated a picture-transmitting system." (Huang and Tretiak, 1965, pp. 45-46). "Computer simulation of a letter generator using the above grammar is a comparatively straightforward programming task. Such a program, making use of COMPAX, has been written for CDC 3600 system at the Tata Institute of Fundamental Research, Bombay." (Narasimhan, 1966, p. 171). At IBM, there has been developed a computer program for image-forming systems simulation (IMSIM/1), so that the photo-optical design engineer can study performance before such systems are actually built (Paris, 1966). 7.37 "The first model developed matches CTSS... Next, a simple, first-come, first-served round-robin scheduling procedure will be substituted. Then, a model which incorporates multiprogramming techniques with the CTSS hardware configuration will be developed. Finally, a simple continuous-time Markov model will be used to represent both single-processor and multiple-processor time-shared systems. . . . "The primary result obtained is that it is possible to successfully model users of interactive computer systems and systems themselves with a good degree of accuracy using relatively simple models." (Scherr, 1965, p. 31). "The final model to be simulated will represent a system in which swapping and processor operation are overlapped. While a program is being run by the processor, the program which was running previously is dumped and the next program to run is loaded. Since loading and dumping cannot occur simultaneously, there must be room in the core memory for at least two complete user programs — the program being dumped or loaded. Should two programs intended to run in sequence not fit together in the core memory, the processor must be stopped to complete the swapping." (Scherr, 1965, pp. 40-41). Other examples of experiments in computer simulation of multiple access and time-shared systems include the following: "The development of the simulation program now provides a first-comefirst-serve queue unloading strategy. Continuing effort, however, will provide for optional strategies, e.g., selecting the data unit with the shortest servicing time, consideration of what flow will minimize idle time at the central processor etc." (Blunt, 1965, p. 15). "Project MAC is using a display to show the dynamic activity of jobs within its scheduling algorithm. Watching this display, one can see jobs moving to higher and lower priority queues as time passes." (Sutherland, 1965, p. 13). 7.38 "A great advance also is the wide application of digital computers for the simulation of recognizing and adaptive systems. Digital simulation extraordinarily facilitates and accelerates conducting experiments in this realm by permitting extremely effective experimental investigations without expenditure of materials and with little time spent." (Kovalevsky, 1965, p. 42). Appendix B. Bibliography Abbas, S. A., H. F. Koehler, T. C. Kwei, H. O. Leilich and Ackoff, R. L., Systems, Organizations, and Interdisciplinary Aines, A. A., The Convergence of the Spearheads, in Toward a Alberga, C. N., String Similarity and Misspellings, Commun. ACM 10, No. 5, 302–313 (May 1967). Alt, F. L., The Standardization of Programming Languages, Proc. 19th National Conf., ACM, Philadelphia, Pa., Aug. 25–27, 1964, pp. B 2-1 to B 2-6 (Assoc. for Computing Machinery, 1964). Alt, F. L. and M. Rubinoff, Eds., Advances in Computers, Vol. 7, 303 p. (Academic Press, New York, 1966). Amdahl, G. M., Multi-Computers Applied to On-Line Systems, in On-Line Computing Systems, Proc. Symp. sponsored by the Univ. of California, Los Angeles, and Informatics, Inc., Los Angeles, Calif., Feb. 2-4, 1965, Ed. E. Burgess, pp. 38-42 (American Data Processing, Inc., Detroit, Mich., 1965). Ammon, G. J. and C. Neitzert, An Experimental 65-Nanosecond Thin Film Scratchpad Memory System, AFIPS Proc. Fall Joint Computer Conf., Vol. 27, Pt. 1, Las Vegas, Nev., Nov. 30Dec. 1, 1965, pp. 649–659 (Spartan Books, Washington, D.C., 1965). Anacker, W., G. F. Bland, P. Pleshko and P. E. Stuckert, On the Design and Performance of a Small 60-Nsec Destructive Readout Magnetic Film Memory, IBM J. Res. & Dev. 10, No. 1, 41-50 (Jan. 1966). Anderson, R., E. Marden and B. Marron, File Organization for a Applebaum, E. L., Implications of the National Register of Microfilm Masters, as Part of a National Preservation Program, Lib. Res. & Tech. Serv. 9, 489-494 (1965). Armstrong, J. A., Fresnel Holograms: Their Imaging Properties and Aberrations, IBM J. Res. & Dev. 9, No. 3, 171–178 (May 1965). Armstrong, R., H. Conrad, P. Ferraiolo and P. Webb, Systems Recovery from Main Frame Errors, AFIPS Proc. Fall Joint Computer Conf., Vol. 31, Anaheim, Calif., Nov. 14-16, 1967, pp. 409-411 (Thompson Books, Washington, D.C., 1967). Aron, J. D., Real-Time Systems in Perspective, IBM Sys. J. 6, 49-67 (1967). Aron, J. D., Information Systems in Perspective, in IBM Proc. Inf. Systems Symp., Washington, D.C., Sept. 4-6, 1968, pp. 3-37 (IBM Corp., 1968). Arora, B. M., D. L. Bitzer, H. G. Slottow and R. H. Wilson, The Plasma Display Panel - A New Device for Information Display and Storage, Rept. No. R-346, 24 p. (Coordinated Science Laboratory, Univ. of Illinois, Urbana, Ill., April 1967). Aschenbrenner, R. A., M. J. Flynn and G. A. Robinson, Intrinsic Multiprocessing, AFIPS Proc. Spring Joint Computer Conf., Vol. 30, Atlantic City, N.J., Apr. 18-20, 1967, pp. 81-86 (Thompson Books, Washington, D.C., 1967). Asendorf, R. H., The Remote Reconnaissance of Extraterrestrial Environments, in Pictorial Pattern Recognition, Proc. Symp. on Automatic Photointerpretation, Washington, D.C., May 31June 2, 1967, Ed. G. C. Cheng et al., pp. 223–238 (Thompson Book Co., Washington, D.C., 1968). Ash, W. L. and E. H. Sibley, TRAMP: An Interpretive Associative Processor with Deductive Capabilities, Proc. 23rd National Conf. ACM, Las Vegas, Nev., Aug. 27–29, 1968, pp. 143-156 (Brandon/Systems Press, Inc., Princeton, N.J., 1968). Auerbach Corporation, Source Data Automation, Final Rept. 1392-200-TR-1, 1 v. (Philadelphia, Pa., Jan. 16, 1967). Austin, C. J., Dissemination of Information and Problems of Graphic Presentation, Proc. 1965 Congress F.I.D. 31st Meeting and Congress, Vol. II, Washington, D.C., Oct. 7-16, 1965, pp. 241-245 (Spartan Books, Washington, D.C., 1966). Avižienis, A., Design of Fault-Tolerant Computers, AFIPS Proc. Fall Joint Computer Conf., Vol. 31, Anaheim, Calif., Nov. 14-16, 1967, pp. 733-743 (Thompson Books, Washington, D.C., 1967). Avižienis, A., A Digital Computer with Automatic_Self-Repair and Majority Vote, Computers & Automation 17, No. 5, 13 (May 1968). Avram, H. D., R. S. Freitag and K. D. Guiles, A Proposed Format for a Standardized Machine-Readable Catalog Record, ISS Planning Memo. No. 3, Preliminary Draft, 110 p. (Library of Congress, Washington, D.C., June 1965). Baker, C. E. and A. D. Rugari, A Large-Screen Real-Time Display Baker, F. T. and W. E. Triest, Advanced Computer Organization, Baker, J. D. and W. A. Kane, Make EDP Controls Work for You, in Data Processing, Vol. X, Proc. 1966 International Data Processing Conf., Chicago, Ill., June 21-24, 1966, pp. 97-100 (Data Processing Management Assoc., 1966). Balzer, R. M., EXDAMS-EXtendable Debugging and Monitoring System, AFIPS Proc. Spring Joint Computer Conf., Vol. 34, |