1. PARALLEL PROCESSING
BYBY
RAFI ULLAH
PhD 1st Semester (Software
Engineering)
University of Malakand Pakistan

2. Contents
 What is Parallel Processing
 Why parallel processing
 How parallel processing divide workload
 Classification Parallel Processor Architectures Classification Parallel Processor Architectures
 Advantages of Parallel processing

3. Parallel processing
 In Parallel processing a single program is run
by multiple processor
 Parallel processing is a form of processing in
which many instructions are carried out
simultaneously operating on the principle
which many instructions are carried out
simultaneously operating on the principle
that large problems can often be divided into
smaller ones, which are then solved
concurrently (in parallel)

4. Parallel processing
 Is the method of evenly distributing computer
processes between two or more computer
processors
This requires a computer with two or more This requires a computer with two or more
processors installed and enabled
 It also requires an operating system capable
of supporting two or more processors, and
software programs capable of evenly
distributing processes between them

5. Why parallel processing
 With the increased use of computers in every
sphere of human activity, computer scientists
are faced with crucial issues today:
 Processing has to be done faster like never
beforebefore
 Larger or complex computation problems
need to be solved
 Early computers one ALU that perform one
operation at a time mean’s Slow processing

6. Why parallel processing
 Increasing the number of transistors as per
Moore’s Law isn’t a solution, as it also increases
the frequency scaling and power consumption
Power consumption has been a major issue Power consumption has been a major issue
recently, as it causes a problem of processor
heating

7. Why Parallel Processing?
 Traditional computers often are not able to
meet performance needs in many applications:
 Simulation of large complex systems in physics,
economy, biology.... etceconomy, biology.... etc
 Distributed data base with search function
 Computer aided design
 Visualization and multimedia

8. Why Parallel Processing?
 Such applications are characterized by a very
large amount of numerical computation and/or
a high quantity of input data
 In order to deliver sufficient performance for
such applications, we can have manysuch applications, we can have many
processors in a single computer
 PP has the potential of being more reliable: if
one processor fails, the system continues to
work at a slightly lower performance

9. Sequential VS Parallel Processing

10. Sequential VS Parallel Processing

11. Solution is……
 The perfect solution is PARALLELISM
 In hardware as well as software

12. How parallel processing divide
workload
 Parallel computing is an evolution of serial
computing
 where the jobs are broken into discrete
parts that can be executed concurrentlyparts that can be executed concurrently
 Each part is further broken down to a
series of instructions
 Instructions from each part execute
simultaneously on different CPUs

13. Classification Parallel Processor
Architectures
 Flynn has classified the computer systems
based on parallelism in the instructions and in
the data streams
These are: These are:
 Single instruction, single dataSingle instruction, single data (SISD)(SISD)
 Single instruction, multiple dataSingle instruction, multiple data (SIMD(SIMD)
 Multiple instruction, single dataMultiple instruction, single data (MISD)(MISD)
 Multiple instruction, multiple dataMultiple instruction, multiple data (MIMD)(MIMD)

14. Single instruction, single data (SISD)

15. Single instruction, single data (SISD)
 A processor that can only do one job at a time
from start to finish.

16. Single instruction, multiple data (SIMD)
 A single machine instruction stream
 Simultaneous execution on different sets of
data
A large number of processing elements A large number of processing elements
 Array and vector processors are the most
common SIMD machines

17. Single instruction, multiple data (SIMD)

18. Single instruction, multiple data (SIMD)
1st figure

19. Single instruction, multiple data (SIMD)
2nd figure

20. Multiple instruction, single data
(MISD)
 In computing, MISD (multiple
instruction, single data)
 is a type of parallel computing architecture
where many functional units perform differentwhere many functional units perform different
operations on the same data

21. Multiple instruction, single data
(MISD)
 Few actual examples of this class of parallel
computer have ever existed i.e. multiple
frequency filters operating on a single signal
streamstream

22. Multiple instruction, single data (MISD)

23. Multiple instruction, single data (MISD)

24. Multiple instruction, multiple data (MIMD)
 Multiple Instruction: every processor may be executing a
different instruction stream
 Multiple Data: every processor may be working with a
different data streamdifferent data stream
 Distributed systems are MIMD architectures
 Most modern computer fall in this category
 Examples are: Super Computer, Network Parallel
Computer etc.

25. Multiple instruction, multiple data (MIMD)

26. Multiple instruction, multiple data (MIMD)

27. Advantages of Parallel processing
 SaveSave timetime andand costcost
 SolveSolve Larger ProblemsLarger Problems (You are ask to do(You are ask to do
1000 Calculus1000 Calculus questions in 1 hour. In facts, I canquestions in 1 hour. In facts, I can
only do 3 question in 1 hours)only do 3 question in 1 hours)only do 3 question in 1 hours)only do 3 question in 1 hours)
 ConcurrencyConcurrency (do multiple things at the same(do multiple things at the same
time)time)
 Can be made highly faultCan be made highly fault--toleranttolerant

28. Advantages of Parallel processing
 Taking advantage of non-local resources
 Overcoming memory constraints
 Parallel nature of the problem, so parallel
models fit it best

29. Application of Parallel Processing
System
 Nuclear physics
 Fluid dynamics
 Weather forecast
 Image processing, Image processing,
 Image synthesis,
 Virtual reality
 Petroleum
 Virtual prototyping
 Biology and genomics

30. Application of Parallel Processing
System
 Business Intelligence
 Banking, Finance,
 Insurance, Risk Analysis
 Regression tests for large software Regression tests for large software

31. Thank YouThank You
Any Question