Concurrent Systems

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Concurrent Systems
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Sequential Processing

• All of the algorithms weve seen so far are
  sequential
• They have one thread of execution
• One step follows another in sequence
• One processor is all that is needed to run the
  algorithm

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A Non-sequential Example

• Consider a house with a burglar alarm system.
• The system continually monitors
• The front door
• The back door
• The sliding glass door
• The door to the deck
• The kitchen windows
• The living room windows
• The bedroom windows
• The burglar alarm is watching all of these at
  once (at the same time).

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Another Non-sequential Example

• Your car has an onboard digital dashboard that
  simultaneously
• Calculates how fast youre going and displays it
  on the speedometer
• Checks your oil level
• Checks your fuel level and calculates
  consumption
• Monitors the heat of the engine and turns on a
  light if it is too hot
• Monitors your alternator to make sure it is
  charging your battery

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Concurrent Systems

• A system in which
• Multiple tasks can be executed at the same time
• The tasks may be duplicates of each other, or
  distinct tasks
• The overall time to perform the series of tasks
  is reduced

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Advantages of Concurrency

• Concurrent processes can reduce duplication in
  code.
• The overall runtime of the algorithm can be
  significantly reduced.
• More real-world problems can be solved than with
  sequential algorithms alone.
• Redundancy can make systems more reliable.

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Disadvantages of Concurrency

• Runtime is not always reduced, so careful
  planning is required
• Concurrent algorithms can be more complex than
  sequential algorithms
• Shared data can be corrupted
• Communications between tasks is needed

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Achieving Concurrency

• Many computers today have more than one processor
  (multiprocessor machines)

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Achieving Concurrency

• Concurrency can also be achieved on a computer
  with only one processor
• The computer juggles jobs, swapping its
  attention to each in turn
• Time slicing allows many users to get CPU
  resources
• Tasks may be suspended while they wait for
  something, such as device I/O

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Concurrency vs. Parallelism

• Concurrency is the execution of multiple tasks at
  the same time, regardless of the number of
  processors.
• Parallelism is the execution of multiple
  processors on the same task.

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Types of Concurrent Systems

• Multiprogramming
• Multiprocessing
• Multitasking
• Distributed Systems

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Multiprogramming

• Share a single CPU among many users or tasks.
• May have a time-shared algorithm or a priority
  algorithm for determining which task to run next
• Give the illusion of simultaneous processing
  through rapid swapping of tasks (interleaving).

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Multiprocessing

• Executes multiple tasks at the same time
• Uses multiple processors to accomplish the tasks
• Each processor may also timeshare among several
  tasks
• Has a shared memory that is used by all the tasks

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Multitasking

• A single user can have multiple tasks running at
  the same time.
• Can be done with one or more processors.
• Used to be rare and for only expensive
  multiprocessing systems, but now most modern
  operating systems can do it.

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Distributed Systems

• Multiple computers working together with no
  central program in charge.

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Distributed Systems

• Advantages
• No bottlenecks from sharing processors
• No central point of failure
• Processing can be localized for efficiency
• Disadvantages
• Complexity
• Communication overhead
• Distributed control

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