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8/16/2019 PP16-lec1-intro1
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Parallel Processingsp2016
lec#1
Dr M Shamim Baig
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Course Information• Prereq: Computer Architecture, Programming in C C!!
• "e t $ef:% Parallel Computers: Architecture & Programming by Rajaraman% Introduction to Parallel Computing ! nd ed" by #rama$ Programming Massi%ely Parallel Processors ! nd d" by 'ir(
• &ra'ing Polic(
) *ui++es : 10 ) Assignments Pro-ect : 1 ) /i'term am : 0 ) inal am : 3
•Instructor: 4r / 5hamim aig ) mail: ms7aig8case.e'u.p9
• "A: mer arooq % mail: umer.farooq8case.e'u.p9 Cell# 0 3 % ;
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Course Intro'uction
• )ith ad%ances in computer architecture* high per+ormance multiprocessor computers ha%e becomereadily a%ailable & a++ordable, As a result* high
per+ormance & supercomputing is accessible to alarge segment o+ industry that -as once restricted tomilitary research & large corporations , .he course iscomprised o+ architecture* algorithms & programming
o+multicore & Parallel computing systems, It +ocuseson design concepts* principles* paradigms* models* per+ormance e%aluation and real li+e applications,
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Parallel ComputingArchitectures
• Current computer architectures areincreasingl( rel(ing upon parallelism toimpro?e performance: ) Pipeline' processing ) /ultiple e ecution units ) /ulti%core processor @Cores ) /an(%core processor @&P ) /utiprocessors @CP s B
) /ulticomputers @PCs or9stations
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Course Contents• Parallel Architecture /o'els:
) Implicit: Pipelining, 5uperscalar B DEI . ) plicit: 5I/4,/I/4, multicore 5/P,
?ector arra( processor, /PP B Clusters
• Parallel /emor( /o'els : ) 5/, 4/, 45/, /A F /A ) Cache Coherence protocols
• Interconnection Fet=or9s @IF : ) 5tatic ?s 4(namic net=or9 topologies ) EAFs ?s 5AFs @/(rinet, Infini7an'
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• Collecti?e Communication Gperations: ) roa'cast, $e'uction, 5catter B &ather
• m7e''ing /apping application to IF
) e,g $ing /esh into H(percu7e & %ice %ersa
• Parallel 4ata Partitioning "echniques
) 14 24 4 ro=%=ise column%=ise
• Parallel Algorithms 4esign, Anal(sis B
Programming mo'els: 5 P/4 /P/4 B P$A/
Course Contents /cont0d
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• /ulticore 5/P programming using Gpen/P
• /essage Passing multicomputer Cluster
programming using /PI
• /assi?el( @'ata Parallel Processing @ /PP
using &P C 4A platform
• Heterogeneous Parallel Computing using
CP B &P @/PI open/P cu'aC together
Course Contents /cont0d
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• Parallel Performance ?aluation
) Parallel Einpac9 stan'ar' test criteria
) Compute Communicate "ime Anal(sis ) 5(stems monitoring measurement tools
• Parallel Performance Ea=s
) Am'hlKs Ea= B &ustafsonKs Ea=
Course Contents /cont0d
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Applications of HPC
1.<
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ses for Parallel Computing:• Historically, parallel computing has been considered to be "the high end of
computing", and has been used to model difficult scientific and engineeringproblems found in the real world .
• Some examples: ) Atmosphere, Earth, En ironment ) Physics ! applied, nuclear, particle, fusion, photonics ) ioscience, iotechnology, #enetics ) Chemistry, $olecular Sciences , #eology, Seismology ) $echanical Engineering ! from prosthetics to spacecraft ) Electrical Engineering ! Circuit %esign, $icroelectronics ) Computer Science & $athematics
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"he ni?erse is Parallel:• Parallel computing is an e?olution of serial computing that
attempts to emulate =hat has al=a(s 7een the state of affairsin the natural =orl':
• man( comple , interrelate' e?ents happening at the sametime, (et =ithin a sequence.
•or e ample: ) #alaxy formation
) Planetary mo ement ) 'eather and ocean patterns
) (ectonic plate drift ) )ush hour traffic ) Automobile assembly line
) uilding space shuttle ) *rdering a hamburger
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ses for Parallel Computing:"o'a(, commercial applications pro?i'e an equal or greater 'ri?ing force in the 'e?elopment of fastercomputers.
"hese applications requireprocessing of large amount of 'atain sophisticate' =a(s .
+or example:•%atabases, data mining•'eb search engines,
Cloud computing•Ad graphics & irtual reality, esp entertainment industry•*il exploration•$edical imaging and diagnosis•Pharmaceutical design
•$anagement of national & multi!national corporations•+inancial & economic modeling• etwor-ed ideo & multi!media technologies•Collaborati e wor- en ironment
•Computational +luid %ynamics•% A research
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ho an' hat . • (op/001org pro ides statistics on parallel computing users in the charts below • Some things to note: Sectors may o erlap 2
) for example, research may be classified research1 )espondents ha e to choose between the two1 ) " ot Specified" is by far the largest application ! probably means multiple applications1
http://top500.org/http://top500.org/
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on eumann Architecture
Comprised of fourmain components:
MemoryControl UnitArithmetic Logic
UnitInput/Output
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serial computing 15
Traditionally, software has een written for serial computation:
To e run on a single computer ha!ing a single C"UA pro lem is ro#en into a discrete series of
instructions$Instructions are e%ecuted one after another$Only one instruction may e%ecute at any moment intime$
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parallel computing Problem
• "he computational pro7lem usuall('emonstrates characteristics such as the
a7ilit( to 7e: ) ro9en apart into 'iscrete pieces of =or9 that
can 7e sol?e' simultaneousl( ) ecute multiple program instructions at an(
moment in time ) 5ol?e' in less time =ith multiple compute
resources than =ith a single compute resource.
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parallel computing 17 In the simplest sense, parallel computing is the simultaneous
use of multiple compute resources to sol!e a computationalpro lem: To e run using multiple C"UsA pro lem is ro#en into discrete parts that can e sol!edconcurrently
&ach part is further ro#en down into a series of instructionsInstructions from each part e%ecute simultaneously ondi'erent C"Us
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'hy 3se ParallelComputing.
• 4imits to serial computing: ) oth ph(sical B practical reasons pose
significant constraints to simpl( 7uil'inge?er faster serial computers @/oors Ea= :• Eimits to miniaturi+ation• "ransmission spee's
• Po=er 4issipation• nerg( consumption• conomic limitations
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