Module 1-Part 1

8/3/2019 Module 1-Part 1

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Mr. S.S. Sayyad

Assistant Professor, ADCET Ashta

[email protected]

Module 1

Introduction to Parallel Processing

Department of CSE, ADCET, Ashta


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Trends towards Parallel Processing

Data Processing

Information

Processing

Knowledge

Processing

Intelligence

Processing

IncreasingVolumesofRaw

Materialtobeprocessed

IncreasingComple

xityand

sophisticationinprocessing



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Trends Towards Parallel Processing

Data processing: data space is largest, including numeric numberin various format, character symbols, and multidimensional

measure

Information processing: Collection of data objects that are

related by some syntactic structure or relation.

Knowledge processing: consist of information items plus somesemantic meanings.

Intelligence processing: is derived from a collection of

knowledge items.



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From Operating Systems point of view, computer systemsare improved in four phases

Batch Programming

Multiprogramming

Time Sharing

Multiprocessing

Parallel Processing is an efficient form of information

processing which emphasizes the exploitation of concurrent

events in the computing process.



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Parallel programming can be challenged in fourprogrammable levels

Job or Program Level

Task or Procedure Level

Inter instruction Level

Intra instruction Level

Hardware Software Trade Offs

Parallel and Distributed processing



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Parallel Computer Architectures

Pipeline Computers: A pipeline computer performsoverlapped computations to exploit temporal parallelism.

Array Processors: An array processor uses multiple

synchronized arithmetic logic units to achieve spatial

parallelism

Multiprocessor Systems: A multiprocessor system achieves

asynchronous parallelism through a set of interactive

processors with shared resources.

Data Flow Computers



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Pipeline

Computer


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Array

Processor


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Multiprocessor Systems


Aimed at : Improving throughput, reliability, flexibility andavailability.

Basic multiprocessor system contain two or more processor.

All processor share access to common sets of memory

module, I/O channels and peripheral devices. Most importantly, whole system is controlled by a single

integrated operating system.

Beside the shared memories and I/O devices, each processor

has its own local memory and private devices. Inter processor communication can be done throw shared

memory or throw interrupt network.


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Data Flow Computers

Programs for Data Driven Computation

Calculation of z= (x+y)*2

Template Implementation

Basic Data Flow Mechanism



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Multiplicity of Instruction Data Streams

Single Instruction Stream- Single Data Stream

Processing Units

Control Units

Memory Modules



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Single Instruction Stream- Multiple Data Stream



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Multiple Instruction Stream- Single Data Stream



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Multiple Instruction Stream- Multiple Data Stream



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Serial v/s Parallel ProcessingFengs

Scheme

Use degree of parallelism to classify various computerarchitectures.

Maximum number of binary digits (bits) that can beprocessed within a unit by a computer system is called the

maximum parallelism degree P. Average Parallelism Degree Equation:

Processing Methods and their Examples (text)

Word Serial Bit Serial

Word Parallel Bit Serial Word Serial Bit Parallel

Word Parallel Bit Serial



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Parallel Processing Applications

Predictive Modeling and Simulations Numerical Weather Forecasting Oceanography and Astrophysics Socioeconomics and government use

Engineering Design and Automation Finite Element Analysis Computational Aerodynamics Artificial Intelligence and Automation Remote Sensing Applications

Medical Military and Basic Research Computer assisted tomography Genetic Engineering Weapon Research and Defense.


Module 1-Part 1

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