Sample Code | |
---|---|
GENERATE 15,5 SEIZE Barber ADVANCE 10,2 RELEASE Barber TERMINATE 1 | |
Designed by | Geoffrey Gordon |
Developer | IBM |
First appeared | 1961 |
Filename extensions | .gps |
Major implementations | |
GPSS World, JGPSS |
General Purpose Simulation System (GPSS) is a simulation language used for discrete-event simulations. It is especially useful in the modelling of queuing systems, with many statistics being collected automatically. [1] The typical simulation consists of Transactions being generated in the system (usually at a certain interval), performing a defined set of rules (like use a resource, wait, transfer), and being removed from the simulation.
GPSS was developed in the 1960s by Geoffrey Gordon, an employee of IBM's Advanced Systems Development Division (ASDD). This division was heavily involved with research into the design of teleprocessing systems, trying to achieve an economic balance of the use of computer resources and shared lines between server terminals. The simulation system, then known as the Gordon Simulator, became very popular in the study of teleprocessing systems within ASDD. It subsequently was fixed and documented on October 25, 1960 in an internal IBM memorandum. [2] Between the winter and summer of 1961, a group of three programmers (including Gordon) rewrote the simulation system with a new algorithm and new block types. It was officially released as a supported IBM-label program on September 27, 1961 with 25 block types. At this point, Gordon stopped working on the simulation system.
In 1963, GPSS II was released with 32 block types. It introduced system numerical attributes, which allowed tracking the current content of a Storage, the length of a Queue, or the current clock time.
In 1965, GPSS III was released. It was made available for IBM Systems 7090/94 and 7040/44.
In 1967, GPSS/360 was released to run on the newly released System 360.
In 1970, GPSS V was released with 49 block types.
In the 1980s, GPSS/VAC and GPSS/PC were released. These appear to be the last official IBM-label releases before the language became unlicensed. [3]
Subsequently, there were releases for IBM 360, [4] Univac 1108, and CDC. [5] [6] [7]
Over time, other implementations were developed for systems including DEC's VAX, a specialized APL version for large-scale Univac systems, [8] and Macintosh. [9]
In 2001, the Windows program GPSS World [10] was released with new features to GPSS. It includes scripting with PLUS (a Pascal-like language), graphical system state displays, graphing, and optimization experiments.
In 2009, a graphical Java-based tool called JGPSS (Java General Purpose Simulation System) was developed to teach the GPSS simulation language. [11] [12]
A GPSS simulation is written in an Assembly-style "block diagram language" with many different single-purpose commands ("Blocks") to control the flow of a Transaction, statistics collection, and variables.
Simulations have Transaction entry points through the GENERATE
command, such as a customer walking into a store. Then, actions are performed through claiming Facilities/Storage (like a cashier), waiting, saving statistics, etc. Finally, the simulated transaction exits the simulation through the TERMINATE
command. Each command verb is referred to as a "control".
Blocks can be facility-oriented (such as machines in a job shop) or transaction-oriented (such parts of work-in-process, signals in electronic components or documents in a bureaucratic procedure). GPSS automatically keep track of statistics for display on a report.
Entities can be broadly classified in Resources, Computational entities and Statistical entities. [13] Resources, like Facilities and Storages represent limited capacity resources. Computational entities, like Ampervariables (variables), Functions and random generators are used to represent the state of Transactions or elements of their environment. Statistical entities, like Queues or Tables (histograms) collect statistical information of interest.
Transactions can :
Along with these main tasks, they can also hold parameters with the ASSIGN command. Transactions are implicitly sectioned off in the code.
There can be multiple transactions in the code that happen at once. A transaction starts with GENERATE and ends with TERMINATE. The code inbetween could potentially be shared between multiple transactions by means of the TRANSFER command, but besides that your transaction lifecycles will be separated. It helps to add whitespace between lines of action of one transaction versus another.
GENERATE 0.1
Transaction generated every 0.1 time unit.
GENERATE 15,4
Transaction is generation every 15 time units, plus or minus 4 time units.
To have a transaction wait, use the ADVANCE command. It has similar arguments to GENERATE.
ADVANCE 10,6
Transaction waits 10+-6 seconds.
To use a Facility, which only allows one use at a time, use the SEIZE command. To stop using it, use the RELEASE command.
GENERATE 30,5 ; Generate a customer every 30+-5 time units SEIZE Barber ; Use a facility ADVANCE 15,4 ; Wait 15+-4 time units RELEASE Barber ; Stop using the facility TERMINATE 1 ; Leave the barber shop
If you want more than one use at a time, use Storage.
Seating STORAGE 100 ; 100 people allowed in lounge seating GENERATE 10,5 ; Generate a person every 10+-5 time units ENTER Seating,1 ; Person sits down ADVANCE 15,4 ; Wait 15+-4 time units LEAVE Barber,1 ; Person stops sitting TERMINATE 1 ; Exit the seating area
This way, multiple people can sit in the Seating at once. If this was a Facility (using SEIZE/RELEASE), it would block others who tried to use the resource.
The ENTER command takes the storage reference as Argument A and the amount to reserve with Argument B. The LEAVE command's arguments are the same.
To remove the transaction, use TERMINATE.
The optional argument decrements the completion counter, which is a variable that is chosen by the user when running the simulation. Say you wanted to test 100 customers: you would start the execution of your simulation with START 100
. TERMINATE 1
at the end of each transaction would decrement initial value 100 by 1 (99, 98, 97 ...) until it reached zero. At this point, the simulation stops and results are returned. If you omit the argument in TERMINATE, it will be assumed to be 0. This means your simulation will run forever (unless, of course, you have another TERMINATE that does decrement this counter.
To have your program run for a predetermined time, make sure none of your TERMINATES decrement the counter and include a section like this:
GENERATE ; Generate one transaction ADVANCE 100 ; Run for 100 time units TERMINATE 1 ; End
Then run your program with START 1. It will run for 100 time units.
Use the ASSIGN control block to assign a value to a transaction parameter. Called with Pj (j=parameter number)
ASSIGN 2,V$Orderqty ;Parameter 2=Order quantity Custwait ADVANCE 5 ;Lead time is 5 days ENTER Stock,P2 ;Stock increases by P2
ASSIGN : ASSIGN Blocks are used to place or modify a value in a Transaction Parameter.
The following example, taken from Simulation using GPSS, [14] is the "Hello world!" of GPSS and will illustrate the main concepts.
The aim is to simulate one day of operation of a barber shop. Customers arrive in a random constant flow, enter the shop, queue if the barber is busy, get their hair cut on a first-come first-served basis, and then leave the shop. We wish to know the average and maximum waiting line, as well as the number of customers.
SIMULATE ; Define model * * Model segment 1 * GENERATE 18,6 ; Customer arrive every 18±6 mn QUEUE Chairs ; Enter the line SEIZE Joe ; Capture the barber DEPART Chairs ; Leave the line ADVANCE 16,4 ; Get a hair cut in 16±4 mn RELEASE Joe ; Free the barber TERMINATE ; Leave the shop * * Model segment 2 * GENERATE 480 ; Timer arrives at time = 480 mn TERMINATE 1 ; Shut off the run * * Control cards * START 1 ; Start one run END ; End model
The "program" is comprised between the SIMULATE
and END
statements, and is divided into "model segments" and "control cards".
The first segment models customers. The GENERATE
block creates a flow of Transactions and schedules them to enter the model with an inter-arrival time uniformly distributed over the range 18±6. It is the programmer's responsibility to interpret these transaction as customers and to understand that the time is to be counted in minutes. The Transactions start their existence in the GENERATE
block and progress from Block to Block, according to certain rules, until they reach a TERMINATE
which remove them from the model.
Normally transactions progress from one block to the next one, so the customer transactions will leave the GENERATE
block to enter the QUEUE Chairs
block. This block simulates a waiting line, and collects statistics accordingly. In the example, it materialize a line of chairs and, at the end of the simulation, we will know, among other things, the maximum queue size (how many chairs are needed) and the average waiting time. The QUEUE
block requires the name of the queue as a parameter, because more than one queue may exist in the model. Each one is associated with a DEPART
block, which is triggered when the transaction leaves the queue. GPSS remembers which transactions are in the queue, so that it possible to know the average time spent, and to check that no buggy transaction is leaving a queue without previously entering in it.
After the QUEUE chairs
block, the transaction will try to proceed to the SEIZE Joe
block, a block simulating the capture of the Facility named Joe. Facilities model single servers of capacity one. If the facility is busy, the SEIZE
will deny the attempting transaction the right to enter. In the example, the customer will wait in the QUEUE
block. If it is free, or as soon as it becomes available, the transaction will be allowed to capture the facility, mark it as busy to others transactions and start to count the service time and other statistics, until the same transaction passes the corresponding RELEASE Joe
block.
The SEIZE
/ RELEASE
pairs are linked by the facility name, because many independent facilities may exist in the model. They can model operators, like a barber, a repairman, an agent, but also pieces of equipment, like a crane, a gas station, an authorization document, etc., in fact anything with capacity one. To simulate multiple parallel servers, like a team of five barbers, or an oven with a capacity of 10, GPSS uses entities named STORAGE
s.
After a customer seizes Joe, she proceeds to the next statement which is ADVANCE 16,4
, whose task is to freeze the entity for a prescribed length of time, here a random number picked between 16-4=12 and 16+4=20mn. Other service time distributions are available through GPSS FUNCTION
(a somehow different notion than function in other programming languages). During that time, other transactions will be allowed to move through the model, blocking some other facilities that may exist in the model, but not Joe because this facility is busy with the frozen customer. After the prescribed time, the customer will wake up, proceed to the next statement, which will free Joe, and TERMINATE
.
Then the next transaction on the previous block, that is a customer sitting on a chair, will be able to SEIZE Joe
. To select the "next" transaction, GPSS uses the first-come first-served basis, with priority. Other selection policies can be programmed by direct manipulation of the future event chain entity.
In parallel to this first segment, simulating the customer behavior, a second model segment simulates the end of the day. At time 480mn = 8h an entity is GENERATE
d, which will TERMINATE
on the next block. This time, the TERMINATE
as a parameter of 1, meaning a special counter is decreased by 1. When that counter reaches 0, the program stops and the output is printed. This special counter is set up with the START
statement. In the example, it is set to one, thus the simulation will finish after one run of 480 mn in simulated time.
The output contains:
FACILITY AVERAGE NUMBER AVERAGE SEIZING PREEMPTING UTILIZATION ENTRIES TIME/TRAN TRANS. NO. TRANS. NO. Joe .860 26 15.884 26 QUEUE MAXIMUM AVERAGE TOTAL ZERO PERCENT AVERAGE $AVERAGE TABLE CURRENT CONTENTS CONTENT ENTRIES ENTRIES ZEROS TIME/TRANS TIME/TRANS NUMBER CONTENTS Chairs 1 .160 27 12 44.4 2.851 5.133 1 $AVERAGE TIME/TRANS = AVERAGE TIME/TRANS EXCLUDING ZERO ENTITIES
It indicates that Joe was busy 86.0% of the time, gave a hair cut to 26 customers and that hair cut took 15.88 minutes on the average. Incidentally, Joe was cutting the hair of customer number 26 when the simulation was closed. No programming provisions were taken for the barber to finish the hair cut before closing the shop.
It indicates also that a maximum of 1 customer was observed waiting his turn, in fact the number of waiting customer was on the average 0.160. A total of 27 customers did enter the queue, so that customer number 27 was still sitting, waiting his turn, when Joe closed the shop. Out of these 27 customers, 12 were served without having to wait. In fact, the queue was empty 44.4% of the time. The average waiting time was 2.851 min, and the average waiting time for the 15=27-12 customers who did really wait was 5.133 min.
* Pg 108 Q 18 * A one-chair unisex hair shop has arrivals at the rate of one every 20+-15 minutes. * One-half of the arriving customers want a dry cuts, 30% want a style, and 20% * want a trim only. A dry cut takes 15+-5 minutes, a style cut takes 25+-10 minutes, * and a trim takes 10+-3 minutes. Simulate 50 customers coming through the hair * shop. Compare the given proportion of service rqequests of each type with the * simulated outcome. Are the results reasonable? Base your answer on the binomial * distribution. Arrivals FUNCTION RN1,D4 ; 1=dry cut, 2=style, 3=trim 0.0,0/0.5,1/0.8,2/1.0,3 GENERATE 20,15 ; Generate arrivals ASSIGN 1,FN$Arrivals ; Assign arrival type to P1 Test1 TEST E P1,1,Test2 ; If P1=1, transfer to DryCut. Else Test2 TRANSFER ,DryCut Test2 TEST E P1,2,TrimHair ; If P1=2, transfer to StyCut. Else Trim. TRANSFER ,StyCut DryCut SEIZE Chair ADVANCE 15,5 SAVEVALUE WantedDryCut+,1 TRANSFER ,Term StyCut SEIZE Chair ADVANCE 25,10 SAVEVALUE WantedStyleCut+,1 TRANSFER ,Term TrimHair SEIZE Chair ADVANCE 10,3 SAVEVALUE WantedTrimHair+,1 Term RELEASE Chair TERMINATE 1
* Pg 108 Q 14 * A superhighway connects one large metropolitan area to another. A vehicle leaves * the first city every 20+-15 seconds. Twenty percent of the vehicles have 1 pass- * enger, 30% of the vehicles have 2 passengers, 10% have 3 passengers, and 10% * have 4 passengers. The remaining 30% of ehicles are buses which carry 40 * people. It takes 60+-10 minutes for a vehicle to travel between the two metro- * politan areas. How long does it take for 5000 people to arrive in the second city? Passenger FUNCTION RN1,D6 0.0,0/0.2,1/0.5,2/0.6,3/0.7,4/1.0,40 GENERATE 20,15 ; New vehicle enters superhighway (seconds) ASSIGN 1,FN$Passenger ; Assign number of passengers to P1 ADVANCE (60#60),(10#60) ; Travel (minutes to seconds) TERMINATE P1 ; Decrease the count by number of passengers * End time is in seconds. Must be divided by 60. * RESULT: 10958 seconds => 182.645 minutes = 3 hr 2 min
Source: [15]
Prefix | Meaning |
---|---|
Pj | A parameter of the transaction current being processed by the program. |
M1 | The transit time of the current transaction. |
MPj | Intermediate transit time of current transaction. |
PR | Priority of current transaction (0-127). |
Prefix | Meaning |
---|---|
CHj | The current count, which is the number of the transaction on a specified user chain. |
CAj | The average number of transactions on user chain j. |
CCj | Total number of entries on user chain j. |
CTj | Average time per transaction on user chain j. |
Prefix | Meaning |
---|---|
Nj | The entry count of the total number of transactions which have entered a specified block in the block diagram. This count is automatically maintained by the program. Example: N$SAM for the entry count at block SAM. This count does not include the transaction currently in process at its current block. |
Wj | The wait count, which is the number of transactions currently waiting at a specified block of the block diagram. This count is also maintained automatically by the program. Example: WSHOLD for the current wait count at block HOLD. This count is also exclusive of the transactions currently in process at its current block. |
Prefix | Meaning |
---|---|
Kj | An indication that the integer is a constant. Example K3276 for the integer 3276 or KO for the integer zero. |
RN(x) | A computed random number (1<=x<=8). The value of the number is an integer between 0 and 999, inclusive, unless the quantity is to be used as the independent variable of a function. In that case, the number is a fraction greater than or equal to zero, but less than one. In either case, all values within the specified range may be considered equally probable. |
C1 | The current value of the simulator clock. This quantity is automatically maintained by the program. |
Prefix | Meaning |
---|---|
Sj | The contents of a specified storage in the block diagram. The quantity may be modified by ENTER and LEAVE blocks. Example: S2 for the contents of storage (number) 2. |
Rj | The number of available units of space in the specified storage. This quantity may be modified by ENTER and LEAVE blocks. Example: R195 for the space remaining in storage 195. |
SRj | Utilization of storage j in parts per thousand, i.e., if the utilization was .65 the computed value would be 650. |
SAj | Average contents of storage j (truncated). |
SMj | Maximum contents of storage j. This quantity is automatically maintained by the program. |
SCj | Number of entries for storage J. This quantity is automatically maintained by the program. |
STj | Average time each transaction used storage j (truncated). |
Prefix | Meaning |
---|---|
Fj | The status of the specified facility in the block diagram. This value is zero if the facility is available; otherwise, it is one. This quantity may be modified by SEIZE, RELEASE, PREEMPT, and RETURN blocks. Example: F20 for the status of facility 20. |
FRj | Utilization of facility j in parts per thousand, i.e., if the utilization was .88 the value of FRj would be 880. |
FCj | Number of entries for facility j. |
FTj | Average time each transaction used facility j (truncated). |
Prefix | Meaning |
---|---|
Gj | The current number of members of group j. |
Prefix | Meaning |
---|---|
Qj | The length of a specified queue in the block diagram. This quantity may be modified by the QUEUE and DEPART blocks. Example: Q50 for the contents of queue 50. |
QAj | Average contents of queue j (truncated). |
QMj | Maximum contents of queue j. This quantity is automatically maintained by the program |
QCj | Number of entries in queue j. Automatically maintained. |
QZj | Number of entries in queue j. Automatically maintained. |
QTj | Average time each transaction was on queue j (including zero entries). When referenced the value will be truncated to an integer. |
QXj | Average time each transaction was on queue j (excluding zero entries). Truncated. |
Prefix | Meaning |
---|---|
TBj | The computed mean value of a specified histogram-type table which is defined by the user. The TABULATE block is used to enter values in one of these tables. Although the computed average can possess a fractional part, it is not retained unless the computed average is to be used as the independent variable of a function. Example: TB42 for the computed mean value of table 42. |
TCj | Number of entries in table j. |
TDj | Computed standard deviation of table j. |
Prefix | Meaning |
---|---|
Xj | The contents of fullword savevalue j. |
XHj | The contents of halfword save-value j. |
MXj(a,b) | The contents of fullword matrix savevalue j, row a, column b. (a and b can be any other SNA) |
MHj(a,b) | The contents of halfword matrix savevalue j, row a, column b. |
Prefix | Meaning |
---|---|
FNj | A computed function value. Only the integer portion is retained except when used as a function modifier in GENERATE, ADVANCE or ASSIGN blocks. |
Vj | An arithmetic combination of Standard Numerical Attributes which is called a variable statement and is defined by the user. Only the integer portion is retained. (See Chapter 4.) |
BVj | The computed value (1 or 0) of Boolean variable j. |
Entity | Symbol | Meaning |
---|---|---|
Transactions | P | Parameter, fullword[halfword] |
PR | Priority | |
M1 | Transit time | |
MP | Parameter transit time | |
Blocks | N | Total entry count |
W | Current count | |
Facilities | F | Boolean 1 or 0 Status of facility |
FR | Utilization (parts/thousarid) | |
FC | Entry count | |
FT | Average time/transaction' | |
Storages | S | Current contents of storage |
R | Remaining contents | |
SR | Utilization (parts/thousand) | |
SA | Average contents• | |
SM | Maximum contents | |
SC | Entry count | |
ST | Average time/transaction• | |
Queues | Q | Current length of queue |
QA | Average contents• | |
QM | Maximum contents | |
QC | Total entry count | |
QZ | Number of zero entries | |
QT | Average time/transaction | |
QX | Average time/transaction excluding zero | |
Tables | TB | Table mean• |
TC | Entry count | |
TD | Standard deviation• | |
Savevaules | X | Fullword savevaluc |
XII | lialfword savevalue | |
Matrix savevalues | M(a,b) | Fullword matrix |
MH(a, b) | Halfword matrix a = row b = column | |
Groups | G | Number of items in group |
User's chains | CA | Average number on chain• |
CH | Current number on chain | |
CM | Maximum number on chain | |
CC | Total entries | |
CT | Average time entry• | |
Functions | FN | Function |
Variables | V | Arithmetic variable |
V | Floating-point variable | |
BV | Boolean variable | |
Random numbers | RN1-RN8 | As function argument, returns 0 to 0.99999. Otherwise, 0.999 |
Clock | C1 | Clock time relative to last RESET or CLEAR card. |
This is used in TEST command.
E | Equal |
G | Greater Than |
GE | Greater Than or Equal |
L | Less Than |
LE | Less Than or Equal |
MAX | Equal to the Largest such attribute of all Transactions in the Group |
MIN | Equal to the Smallest such attribute of all Transactions in the Group |
NE | Unequal to the reference value specified by Operand E |
The erlang is a dimensionless unit that is used in telephony as a measure of offered load or carried load on service-providing elements such as telephone circuits or telephone switching equipment. A single cord circuit has the capacity to be used for 60 minutes in one hour. Full utilization of that capacity, 60 minutes of traffic, constitutes 1 erlang.
Simula is the name of two simulation programming languages, Simula I and Simula 67, developed in the 1960s at the Norwegian Computing Center in Oslo, by Ole-Johan Dahl and Kristen Nygaard. Syntactically, it is an approximate superset of ALGOL 60, and was also influenced by the design of Simscript.
Queueing theory is the mathematical study of waiting lines, or queues. A queueing model is constructed so that queue lengths and waiting time can be predicted. Queueing theory is generally considered a branch of operations research because the results are often used when making business decisions about the resources needed to provide a service.
In computer science, the sleeping barber problem is a classic inter-process communication and synchronization problem that illustrates the complexities that arise when there are multiple operating system processes.
IBM CICS is a family of mixed-language application servers that provide online transaction management and connectivity for applications on IBM mainframe systems under z/OS and z/VSE.
Simulink is a MATLAB-based graphical programming environment for modeling, simulating and analyzing multidomain dynamical systems. Its primary interface is a graphical block diagramming tool and a customizable set of block libraries. It offers tight integration with the rest of the MATLAB environment and can either drive MATLAB or be scripted from it. Simulink is widely used in automatic control and digital signal processing for multidomain simulation and model-based design.
Record locking is the technique of preventing simultaneous access to data in a database, to prevent inconsistent results.
Tuxedo is a middleware platform used to manage distributed transaction processing in distributed computing environments. Tuxedo is a transaction processing system or transaction-oriented middleware, or enterprise application server for a variety of systems and programming languages. Developed by AT&T in the 1980s, it became a software product of Oracle Corporation in 2008 when they acquired BEA Systems. Tuxedo is now part of the Oracle Fusion Middleware.
In computer science, software transactional memory (STM) is a concurrency control mechanism analogous to database transactions for controlling access to shared memory in concurrent computing. It is an alternative to lock-based synchronization. STM is a strategy implemented in software, rather than as a hardware component. A transaction in this context occurs when a piece of code executes a series of reads and writes to shared memory. These reads and writes logically occur at a single instant in time; intermediate states are not visible to other (successful) transactions. The idea of providing hardware support for transactions originated in a 1986 paper by Tom Knight. The idea was popularized by Maurice Herlihy and J. Eliot B. Moss. In 1995, Nir Shavit and Dan Touitou extended this idea to software-only transactional memory (STM). Since 2005, STM has been the focus of intense research and support for practical implementations is growing.
Microsimulation is the use of computerized analytical tools to perform analysis of activities such as highway traffic flowing through an intersection, financial transactions, or pathogens spreading disease through a population on the granularity level of individuals. Synonyms include microanalytic simulation and microscopic simulation. Microsimulation, with its emphasis on stochastic or rule-based structures, should not be confused with the similar complementary technique of multi-agent simulation, which focuses more on the behaviour of individuals.
A transaction processing system (TPS) is a software system, or software/hardware combination, that supports transaction processing.
A discrete-event simulation (DES) models the operation of a system as a (discrete) sequence of events in time. Each event occurs at a particular instant in time and marks a change of state in the system. Between consecutive events, no change in the system is assumed to occur; thus the simulation time can directly jump to the occurrence time of the next event, which is called next-event time progression.
Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mock up of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome.
In queueing theory, a discipline within the mathematical theory of probability, an M/M/1 queue represents the queue length in a system having a single server, where arrivals are determined by a Poisson process and job service times have an exponential distribution. The model name is written in Kendall's notation. The model is the most elementary of queueing models and an attractive object of study as closed-form expressions can be obtained for many metrics of interest in this model. An extension of this model with more than one server is the M/M/c queue.
VS/9 is a computer operating system for the UNIVAC Series 90 mainframes, used during the late 1960s through 1980s. The 90/60 and 90/70 were repackaged Univac 9700 computers. After the RCA acquisition by Sperry, it was determined that the RCA TSOS operating system was far more advanced than the Univac counterpart, so the company opted to merge the Univac hardware with the RCA software and introduced the 90/70. The 90/60 was introduced shortly thereafter as a slower, less expensive 90/70. It was not until the introduction of the 90/80 that VS/9 finally had a hardware platform optimized to take full advantage of its capability to allow both interactive and batch operations on the same computer.
In queueing theory, a discipline within the mathematical theory of probability, mean value analysis (MVA) is a recursive technique for computing expected queue lengths, waiting time at queueing nodes and throughput in equilibrium for a closed separable system of queues. The first approximate techniques were published independently by Schweitzer and Bard, followed later by an exact version by Lavenberg and Reiser published in 1980.
OS 2200 is the operating system for the Unisys ClearPath Dorado family of mainframe systems. The operating system kernel of OS 2200 is a lineal descendant of Exec 8 for the UNIVAC 1108 and was previously known as OS 1100. Documentation and other information on current and past Unisys systems can be found on the Unisys public support website.
SimEvents is a discrete event simulation tool developed by MathWorks. It adds a library of graphical building blocks for modeling queuing systems to the Simulink environment. It also adds an event-based simulation engine to the time-based simulation engine in Simulink
Traffic simulation or the simulation of transportation systems is the mathematical modeling of transportation systems through the application of computer software to better help plan, design, and operate transportation systems. Simulation of transportation systems started in the 1950s, and is an important area of discipline in traffic engineering and transportation planning today. Various national and local transportation agencies, academic institutions and consulting firms use simulation to aid in their management of transportation networks.
In queueing theory, a discipline within the mathematical theory of probability, an M/G/1 queue is a queue model where arrivals are Markovian, service times have a General distribution and there is a single server. The model name is written in Kendall's notation, and is an extension of the M/M/1 queue, where service times must be exponentially distributed. The classic application of the M/G/1 queue is to model performance of a fixed head hard disk.
In developing GPSS there was no conscious effort to base the design on analog computers, but I feel sure the block diagram notation and the emphasis on making the simulation directly accessible to system analysts rather than through programmers, that are characteristics of GPSS, were unconsciously influenced by the analog computer experience.
IBM has available GPSS III for the 7044 and 7090 series and GPSS/360 for the larger 360 ... GPSS II has also been available on the UNIVAC 1108
about the simulation modeling language GPSS. ... summarized; sources comparing GPSS and other .... Corporation's GPSS for Univac 1108 hardware)
Background: The General Purpose Simulation System (GPSS) is a ... manufacturers that have produced versions of GPSS are UNIVAC (Gorchow, 1968), CDC
GPSS-like ... in the APL version of GPSS, although APL happens to be an interpretive language. ... Univac Corporation, GPSS 1100 for UNIVAC 1108 system.
simplify the development of a complete simulation tool following the GPSS syntax. This paper presents ... In the original, GPSS meant Gordon's Programmable Simulation System, in honor of Geoffrey Gordon, its creator.
Learn simulation building a simulation engine. JGPSS is an implementation of the GPSS system based in Java.