SlideShare a Scribd company logo
1 of 18
1
Parallel Processing
B.Kohila
I-Msc(IT)
2
Topics Covered
 An Overview of Parallel Processing
 Parallelism in Uniprocessor Systems
 Organization of Multiprocessor
 Flynn’s Classification
 System Topologies
 MIMD System Architectures
3
An Overview of Parallel
Processing
 What is parallel processing?
 Parallel processing is a method to improve computer
system performance by executing two or more
instructions simultaneously.
 The goals of parallel processing.
 One goal is to reduce the “wall-clock” time or the
amount of real time that you need to wait for a problem
to be solved.
 Another goal is to solve bigger problems that might not
fit in the limited memory of a single CPU.
4
Parallelism in Uniprocessor Systems
 It is possible to achieve parallelism with a
uniprocessor system.
 Some examples are the instruction pipeline, arithmetic
pipeline, I/O processor.
 Note that a system that performs different
operations on the same instruction is not
considered parallel.
 Only if the system processes two different
instructions simultaneously can it be considered
parallel.
5
Parallelism in a Uniprocessor
System
 A reconfigurable arithmetic pipeline is an example
of parallelism in a uniprocessor system.
Each stage of a reconfigurable arithmetic pipeline has a
multiplexer at its input. The multiplexer may pass input
data, or the data output from other stages, to the stage
inputs. The control unit of the CPU sets the select
signals of the multiplexer to control the flow of data,
thus configuring the pipeline.
6
Vector Arithmetic Unit
A vector arithmetic unit contains multiple
functional units that perform addition, subtraction,
and other functions. The control unit routes input
values to the different functional units to allow the
CPU to execute multiple instructions
simultaneously.
For the operations AB+C and DE-F, the
CPU would route B and C to an adder and then
route E and F to a subtractor for simultaneous
execution.
7
Organization of Multiprocessor
Systems
 Flynn’s Classification
 Was proposed by researcher Michael J. Flynn in 1966.
 It is the most commonly accepted taxonomy of
computer organization.
 In this classification, computers are classified by
whether it processes a single instruction at a time or
multiple instructions simultaneously, and whether it
operates on one or multiple data sets.
8
Single Instruction, Single Data
(SISD)
 SISD machines executes a single instruction on
individual data values using a single processor.
 Based on traditional Von Neumann uniprocessor
architecture, instructions are executed sequentially
or serially, one step after the next.
 Until most recently, most computers are of SISD
type.
9
SISD
Simple Diagrammatic Representation
10
Single Instruction, Multiple
Data (SIMD)
 An SIMD machine executes a single instruction
on multiple data values simultaneously using
many processors.
 Since there is only one instruction, each processor
does not have to fetch and decode each
instruction. Instead, a single control unit does the
fetch and decoding for all processors.
 SIMD architectures include array processors.
11
SIMD
Simple Diagrammatic Representation
12
Multiple Instruction, Multiple
Data (MIMD)
 MIMD machines are usually referred to as
multiprocessors or multicomputers.
 It may execute multiple instructions
simultaneously, contrary to SIMD machines.
 Each processor must include its own control unit
that will assign to the processors parts of a task or
a separate task.
 It has two subclasses: Shared memory and
distributed memory
13
Multiple Instruction, Single
Data (MISD)
 This category does not actually exist. This
category was included in the taxonomy for
the sake of completeness.
14
System Topologies
Topologies
 A system may also be classified by its
topology.
 A topology is the pattern of connections
between processors.
 The cost-performance tradeoff determines
which topologies to use for a multiprocessor
system.
15
Topology Classification
 A topology is characterized by its diameter, total
bandwidth, and bisection bandwidth
– Diameter – the maximum distance between two
processors in the computer system.
– Total bandwidth – the capacity of a communications
link multiplied by the number of such links in the
system.
– Bisection bandwidth – represents the maximum data
transfer that could occur at the bottleneck in the
topology.
16
Uniform memory access
(UMA)
 The UMA is a type of symmetric
multiprocessor, or SMP, that has two or
more processors that perform symmetric
functions. UMA gives all CPUs equal
(uniform) access to all memory locations in
shared memory. They interact with shared
memory by some communications
mechanism like a simple bus or a complex
multistage interconnection network.
17
Nonuniform memory access
(NUMA)
 NUMA architectures, unlike UMA
architectures do not allow uniform access to
all shared memory locations. This
architecture still allows all processors to
access all shared memory locations but in a
nonuniform way, each processor can access
its local shared memory more quickly than
the other memory modules not next to it.
18
Nonuniform memory access
(NUMA) Architecture
Memory 1
Processor 1
Communications mechanism
Memory 2
Processor 2
Memory n
Processor n

More Related Content

What's hot

Cache memory
Cache memoryCache memory
Cache memory
Anuj Modi
 
Dma transfer
Dma transferDma transfer
Dma transfer
gmnithya
 

What's hot (20)

Computer architecture multi processor
Computer architecture multi processorComputer architecture multi processor
Computer architecture multi processor
 
Cache memory
Cache memoryCache memory
Cache memory
 
Parallel Processing Concepts
Parallel Processing Concepts Parallel Processing Concepts
Parallel Processing Concepts
 
Multiprocessor system
Multiprocessor system Multiprocessor system
Multiprocessor system
 
Modes of data transfer
Modes of data transferModes of data transfer
Modes of data transfer
 
Dma transfer
Dma transferDma transfer
Dma transfer
 
Lecture 1 introduction to parallel and distributed computing
Lecture 1   introduction to parallel and distributed computingLecture 1   introduction to parallel and distributed computing
Lecture 1 introduction to parallel and distributed computing
 
Message passing in Distributed Computing Systems
Message passing in Distributed Computing SystemsMessage passing in Distributed Computing Systems
Message passing in Distributed Computing Systems
 
Parallel computing
Parallel computingParallel computing
Parallel computing
 
Lecture 01 introduction to compiler
Lecture 01 introduction to compilerLecture 01 introduction to compiler
Lecture 01 introduction to compiler
 
Dma
DmaDma
Dma
 
Instruction pipeline: Computer Architecture
Instruction pipeline: Computer ArchitectureInstruction pipeline: Computer Architecture
Instruction pipeline: Computer Architecture
 
Cache coherence ppt
Cache coherence pptCache coherence ppt
Cache coherence ppt
 
Basic ops concept of comp
Basic ops  concept of compBasic ops  concept of comp
Basic ops concept of comp
 
Introduction to parallel processing
Introduction to parallel processingIntroduction to parallel processing
Introduction to parallel processing
 
Multi Processors And Multi Computers
 Multi Processors And Multi Computers Multi Processors And Multi Computers
Multi Processors And Multi Computers
 
Direct Memory Access(DMA)
Direct Memory Access(DMA)Direct Memory Access(DMA)
Direct Memory Access(DMA)
 
Multiplexing in mobile computing
Multiplexing in mobile computingMultiplexing in mobile computing
Multiplexing in mobile computing
 
Process scheduling
Process schedulingProcess scheduling
Process scheduling
 
Routing algorithm
Routing algorithmRouting algorithm
Routing algorithm
 

Similar to Parallel processing

Computing notes
Computing notesComputing notes
Computing notes
thenraju24
 
Lecture 2
Lecture 2Lecture 2
Lecture 2
Mr SMAK
 

Similar to Parallel processing (20)

Chapter 10
Chapter 10Chapter 10
Chapter 10
 
Parallel Processing
Parallel ProcessingParallel Processing
Parallel Processing
 
Module 2.pdf
Module 2.pdfModule 2.pdf
Module 2.pdf
 
Distributed system lectures
Distributed system lecturesDistributed system lectures
Distributed system lectures
 
Parallel computing persentation
Parallel computing persentationParallel computing persentation
Parallel computing persentation
 
intro, definitions, basic laws+.pptx
intro, definitions, basic laws+.pptxintro, definitions, basic laws+.pptx
intro, definitions, basic laws+.pptx
 
parallel computing.ppt
parallel computing.pptparallel computing.ppt
parallel computing.ppt
 
Real-Time Scheduling Algorithms
Real-Time Scheduling AlgorithmsReal-Time Scheduling Algorithms
Real-Time Scheduling Algorithms
 
Operating System Lecture 4
Operating System Lecture 4Operating System Lecture 4
Operating System Lecture 4
 
Parallel processing
Parallel processingParallel processing
Parallel processing
 
Parallel Processing.pptx
Parallel Processing.pptxParallel Processing.pptx
Parallel Processing.pptx
 
Unit 5 lect-3-multiprocessor
Unit 5 lect-3-multiprocessorUnit 5 lect-3-multiprocessor
Unit 5 lect-3-multiprocessor
 
System on chip architectures
System on chip architecturesSystem on chip architectures
System on chip architectures
 
Classification of Parallel Computers.pptx
Classification of Parallel Computers.pptxClassification of Parallel Computers.pptx
Classification of Parallel Computers.pptx
 
Multiprocessor
Multiprocessor Multiprocessor
Multiprocessor
 
Operating Systems
Operating Systems Operating Systems
Operating Systems
 
Operating Systems
Operating SystemsOperating Systems
Operating Systems
 
Computing notes
Computing notesComputing notes
Computing notes
 
Lecture 2
Lecture 2Lecture 2
Lecture 2
 
100-E
100-E100-E
100-E
 

More from rajshreemuthiah (20)

oracle
oracleoracle
oracle
 
quality
qualityquality
quality
 
bigdata
bigdatabigdata
bigdata
 
polymorphism
polymorphismpolymorphism
polymorphism
 
solutions and understanding text analytics
solutions and understanding text analyticssolutions and understanding text analytics
solutions and understanding text analytics
 
interface
interfaceinterface
interface
 
Testing &ampdebugging
Testing &ampdebuggingTesting &ampdebugging
Testing &ampdebugging
 
concurrency control
concurrency controlconcurrency control
concurrency control
 
Education
EducationEducation
Education
 
Formal verification
Formal verificationFormal verification
Formal verification
 
Transaction management
Transaction management Transaction management
Transaction management
 
Multi thread
Multi threadMulti thread
Multi thread
 
System testing
System testingSystem testing
System testing
 
software maintenance
software maintenancesoftware maintenance
software maintenance
 
exception handling
exception handlingexception handling
exception handling
 
e governance
e governancee governance
e governance
 
recovery management
recovery managementrecovery management
recovery management
 
Implementing polymorphism
Implementing polymorphismImplementing polymorphism
Implementing polymorphism
 
Buffer managements
Buffer managementsBuffer managements
Buffer managements
 
os linux
os linuxos linux
os linux
 

Recently uploaded

IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
Enterprise Knowledge
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
 

Recently uploaded (20)

Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfTech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
 

Parallel processing

  • 2. 2 Topics Covered  An Overview of Parallel Processing  Parallelism in Uniprocessor Systems  Organization of Multiprocessor  Flynn’s Classification  System Topologies  MIMD System Architectures
  • 3. 3 An Overview of Parallel Processing  What is parallel processing?  Parallel processing is a method to improve computer system performance by executing two or more instructions simultaneously.  The goals of parallel processing.  One goal is to reduce the “wall-clock” time or the amount of real time that you need to wait for a problem to be solved.  Another goal is to solve bigger problems that might not fit in the limited memory of a single CPU.
  • 4. 4 Parallelism in Uniprocessor Systems  It is possible to achieve parallelism with a uniprocessor system.  Some examples are the instruction pipeline, arithmetic pipeline, I/O processor.  Note that a system that performs different operations on the same instruction is not considered parallel.  Only if the system processes two different instructions simultaneously can it be considered parallel.
  • 5. 5 Parallelism in a Uniprocessor System  A reconfigurable arithmetic pipeline is an example of parallelism in a uniprocessor system. Each stage of a reconfigurable arithmetic pipeline has a multiplexer at its input. The multiplexer may pass input data, or the data output from other stages, to the stage inputs. The control unit of the CPU sets the select signals of the multiplexer to control the flow of data, thus configuring the pipeline.
  • 6. 6 Vector Arithmetic Unit A vector arithmetic unit contains multiple functional units that perform addition, subtraction, and other functions. The control unit routes input values to the different functional units to allow the CPU to execute multiple instructions simultaneously. For the operations AB+C and DE-F, the CPU would route B and C to an adder and then route E and F to a subtractor for simultaneous execution.
  • 7. 7 Organization of Multiprocessor Systems  Flynn’s Classification  Was proposed by researcher Michael J. Flynn in 1966.  It is the most commonly accepted taxonomy of computer organization.  In this classification, computers are classified by whether it processes a single instruction at a time or multiple instructions simultaneously, and whether it operates on one or multiple data sets.
  • 8. 8 Single Instruction, Single Data (SISD)  SISD machines executes a single instruction on individual data values using a single processor.  Based on traditional Von Neumann uniprocessor architecture, instructions are executed sequentially or serially, one step after the next.  Until most recently, most computers are of SISD type.
  • 10. 10 Single Instruction, Multiple Data (SIMD)  An SIMD machine executes a single instruction on multiple data values simultaneously using many processors.  Since there is only one instruction, each processor does not have to fetch and decode each instruction. Instead, a single control unit does the fetch and decoding for all processors.  SIMD architectures include array processors.
  • 12. 12 Multiple Instruction, Multiple Data (MIMD)  MIMD machines are usually referred to as multiprocessors or multicomputers.  It may execute multiple instructions simultaneously, contrary to SIMD machines.  Each processor must include its own control unit that will assign to the processors parts of a task or a separate task.  It has two subclasses: Shared memory and distributed memory
  • 13. 13 Multiple Instruction, Single Data (MISD)  This category does not actually exist. This category was included in the taxonomy for the sake of completeness.
  • 14. 14 System Topologies Topologies  A system may also be classified by its topology.  A topology is the pattern of connections between processors.  The cost-performance tradeoff determines which topologies to use for a multiprocessor system.
  • 15. 15 Topology Classification  A topology is characterized by its diameter, total bandwidth, and bisection bandwidth – Diameter – the maximum distance between two processors in the computer system. – Total bandwidth – the capacity of a communications link multiplied by the number of such links in the system. – Bisection bandwidth – represents the maximum data transfer that could occur at the bottleneck in the topology.
  • 16. 16 Uniform memory access (UMA)  The UMA is a type of symmetric multiprocessor, or SMP, that has two or more processors that perform symmetric functions. UMA gives all CPUs equal (uniform) access to all memory locations in shared memory. They interact with shared memory by some communications mechanism like a simple bus or a complex multistage interconnection network.
  • 17. 17 Nonuniform memory access (NUMA)  NUMA architectures, unlike UMA architectures do not allow uniform access to all shared memory locations. This architecture still allows all processors to access all shared memory locations but in a nonuniform way, each processor can access its local shared memory more quickly than the other memory modules not next to it.
  • 18. 18 Nonuniform memory access (NUMA) Architecture Memory 1 Processor 1 Communications mechanism Memory 2 Processor 2 Memory n Processor n