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```Chapter 3
System
Performance
and Models
3.1 Introduction
• A system is the part of the real world under
study. Composed of a set of entities
interacting among themselves and with the
environment.
• A model is an abstract representation of a
system.
• The system behavior is dependent on the
input data and actions from the
environment.
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• Abstraction
– The most important concept in analysis and
design
– A high-level description of a collection of
objects
– Only the relevant properties and features of
the objects are included.
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System
A system has:
• Structure
• Behavior
The model of a system is simpler than the real
system in its structure and behavior. But it
should be equivalent to the system.
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Using Models
A user can:
• Manipulate the model by supplying it with a
set of inputs
• Observe its behavior or output
• Predict the behavior of the real system by
analyzing the behavior of the model.
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Behavior of a Model
Depends on:
• The passage of time
• Input data
• Events generated by the environment
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3.2 General Concepts of Model
The most general categories of models are:
• Physical models (scale models)
• Graphical models
• Mathematical models.
Mathematical models are the most flexible
ones.
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3.3 Simple Models of Computer Systems
Model of a Simple Batch System
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Simulation Results
For every simulation run there are two types of
output:
• Trace - sequence of events that occur during
the simulation period
• Performance measures - summary statistics
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3.4 Performance of Computer Systems
• Measures that indicate how well (or bad) the
system is being studied carrying out its
functions, with respect to some aspects
• In studying a system, usually several
performance measures are necessary.
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Approaches for Studying Performance
• Measurements on the real system
• Simulation models
• Analytical (mathematical) models
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Performance Study
A complete performance study includes the
definition of the following components:
– A set of relevant objectives and goals
– Performance metrics
– System parameters
– System factors
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3.4.1 Performance Measures
• Average wait time: the average period that jobs wait in system
since their arrival time
• Average throughput: average number of jobs completed in
some specified time interval.
• CPU Utilization: the portion of time the CPU is used relative to
total observation interval.
• Resource Utilization: the proportion of the interval the
resource is used.
• Response time: the average time interval that the system
takes to respond to a particular command or request of a user
process.
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Performance Measures (cont’d)
• Average turnaround time: the average time interval that
elapses from the time a job is submitted until the time the
system writes the output results (also called sojourn time).
• Availability: the fraction of time that an external observer
finds the system capable of carrying out some work.
• Reliability: the mean time between failures.
• Capacity: maximum achievable throughput under ideal
• Fairness: a measure of the variability of throughput across the
various types of jobs or processes.
• Speedup: a factor of gains in speed usually achieved by adding
more processors to a system.
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Goal of Performance Study
• Reduce waiting periods for the processes
• Improve the processor utilization
• Maximize throughput
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(These are for the simulation model, Skip )
• The performance measures depend on the
• The workload for a system can be characterized
by another series of measures, which are made
on the input to the system
• Errors in characterizing the workload may have
serious consequences.
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Inter-arrival time
I/O request rate
I/O service rate
Memory request
System Parameters
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System memory
Processor speed
Number and type of processors
Degree of multi-programming
Length of time slice
Number and type of I/O ports
Skip: 3.5 and 3.6 (Run simulator)
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3.7 System Capacity and Bottleneck
• The capacity of a system is determined by its
maximum performance
• The nominal capacity of a system is given by the
maximum achievable throughput under ideal
conditions
• The usable capacity is the maximum throughput
achievable under specified constraints.
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Bottleneck
• The computer system reaches capacity when one
or more of its servers or resources reach a
utilization close to 100%.
• The bottleneck of the system will be localized in
the server or resource with a utilization close to
100%, while the other servers and resources each
have utilization significantly below 100%.
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