Computer architecture

MICROPROCESSOR
• IT IS ONE OF THE GREATEST
ACHIEVEMENTS OF THE 20TH
CENTURY.
• IT USHERED IN THE ERA OF WIDESPREAD
COMPUTERIZATION.

EARLY ARCHITECTURE
• VON NEUMANN ARCHITECTURE, 1940
• PROGRAM IS STORED IN MEMORY.
• SEQUENTIAL OPERATION
• ONE INST IS RETRIEVED AT A TIME, DECODED
AND EXECUTED
• LIMITED SPEED

Conventional 32 bit
Microprocessors
• Higher data throughput with 32 bit wide data bus
• Larger direct addressing range
• Higher clock frequencies and operating speeds as a result
of improvements in semiconductor technology
• Higher processing speeds because larger registers require
fewer calls to memory and reg-to-reg transfers are 5 times
faster than reg-to-memory transfers

Conventional 32 bit
Microprocessors
• More insts and addressing modes to improve software
efficiency
• More registers to support High-level languages
• More extensive memory management & coprocessor
capabilities
• Cache memories and inst pipelines to increase processing
speed and reduce peak bus loads

Conventional 32 bit
Microprocessors
• To construct a complete general purpose 32 bit
microprocessor, five basic functions are necessary:
 ALU
 MMU
 FPU
 INTERRUPT CONTROLLER
 TIMING CONTROL

Conventional Architecture
• KNOWN AS VON NEUMANN ARCHITECTURE
• ITS MAIN FEATURES ARE:
 A SINGLE COMPUTING ELEMENT INCORPORATING A
PROCESSOR, COMM. PATH AND MEMORY
 A LINEAR ORGANIZATION OF FIXED SIZE MEMORY
CELLS
 A LOW-LEVEL MACHINE LANGUAGE WITH INSTS
PERFORMING SIMPLE OPERATIONS ON ELEMENTARY
OPERANDS
 SEQUENTIAL, CENTRALIZED CONTROL OF
COMPUTATION

• Single processor configuration:
PROCESSOR
MEMORY INPUT-OUTPUT

• Multiple processor configuration with a global bus:
SYSTEM
INPUT-
OUTPUT
GLOBAL
MEMORY
PROCESSORS
WITH LOCAL
MEM & I/O

• THE EARLY COMP ARCHITECTURES WERE
DESIGNED FOR SCIENTIFIC AND COMMERCIAL
CALCULATIONS AND WERE DEVEPOED TO
INCREASE THE SPEED OF EXECUTION OF SIMPLE
INSTRUCTIONS.
• TO MAKE THE COMPUTERS PERFORM MORE
COMPLEX PROCESSES, MUCH MORE COMPLEX
SOFTWARE WAS REQUIRED.

• ADVANCEMENT OF TECHNOLOGY ENHANCED
THE SPEED OF EXECUTION OF PROCESSORS BUT
A SINGLE COMM PATH HAD TO BE USED TO
TRANSFER INSTS AND DATA BETWEEN THE
PROCESSOR AND THE MEMORY.
• MEMORY SIZE INCREASED. THE RESULT WAS
THE DATA TRANSFER RATE ON THE MEMORY
INTERFACE ACTED AS A SEVERE CONSTRAINT
ON THE PROCESSING SPEED.

• AS HIGHER SPEED MEMORY BECAME
AVAILABLE, THE DELAYS INTRODUCED BY THE
CAPACITANCE AND THE TRANSMISSION LINE
DELAYS ON THE MEMORY BUS AND THE
PROPAGATION DELAYS IN THE BUFFER AND
ADDRESS DECODING CIRCUITRY BECAME MORE
SIGNIFICANT AND PLACED AN UPPER LIMIT ON
THE PROCESSING SPEED.

• THE USE OF MULTIPROCESSOR BUSES WITH THE
NEED FOR ARBITRATION BETWEEN COMPUTERS
REQUESTING CONTROL OF THE BUS REDUCED
THE PROBLEM BUT INTRODUCED SEVERAL WAIT
CYCLES WHILE THE DATA OR INST WERE
FETCHED FROM MEMORY.
• ONE METHOD OF INCREASING PROCESSING
SPEED AND DATA THROUGHPUT ON THE
MEMORY BUS WAS TO INCREASE THE NUMBER
OF PARALLEL BITS TRANSFERRED ON THE BUS.

• THE GLOBAL BUS AND THE GLOBAL MEMORY
CAN ONLY SERVE ONE PROCESSOR AT A TIME.
• AS MORE PROCESSORS ARE ADDED TO
INCREASE THE PROCESSING SPEED, THE GLOBAL
BUS BOTTLENECK BECAME WORSE.
• IF THE PROCESSING CONSISTS OF SEVERAL
INDEPENDENT TASKS, EACH PROC WILL
COMPETE FOR GLOBAL MEMORY ACCESS AND
GLOBAL BUS TRANSFER TIME.

• TYPICALLY, ONLY 3 OR 4 TIMES THE SPEED OF A
SINGLE PROCESSOR CAN BE ACHIEVED IN
MULTIPROCESSOR SYSTEMS WITH GLOBAL MEMORY
AND A GLOBAL BUS.
• TO REDUCE THE EFFECT OF GLOBAL MEMORY BUS AS A
BOTTLENECK, (1) THE LENGTH OF THE PIPE WAS
INCREASED SO THAT THE INST COULD BE BROKEN
DOWN INTO BASIC ELEMENTS TO BE MANIPULATED
SIMULTANEOUSLY AND (2) CACHE MEM WAS
INTRODUCED SO THAT INSTS AND/OR DATA COULD BE
PREFETCHED FROM GLOBAL MEMORY AND STORED IN
HIGH SPEED LOCAL MEMORY.

PIPELINING
• THE PROC. SEPARATES EACH INST INTO ITS BASIC
OPERATIONS AND USES DEDICATED EXECUTION UNITS
FOR EACH TYPE OF OPERATION.
• THE MOST BASIC FORM OF PIPELINING IS TO PREFETCH
THE NEXT INSTRUCTION WHILE SIMULTANEOULY
EXECUTING THE PREVIOUS INSTRUCTION.
• THIS MAKES USE OF THE BUS TIME WHICH WOULD
OTHERWISE BE WASTED AND REDUCES INSTRUCTION
EXECUTION TIME.

PIPELINING
• TO SHOW THE USE OF A PIPELINE, CONSIDER THE
MULTIPLICATION OF 2 DECIMAL NOS: 3.8 X 102
AND
9.6X103
. THE PROC. PERFORMS 3 OPERATIONS:
• A: MULTIPLIES THE MANTISSA
• B: ADDS THE EXPONENTS
• C: NORMALISES THE RESULT TO PLACE THE DECIMAL
POINT IN THE CORRECT POSITION.
• IF 3 EXECUTION UNITS PERFORMED THESE
OPERATIONS, OPS.A & B WOULD DO NOTHING WHILE C
IS BEING PERFORMED.
• IF A PIPELINE WERE IMPLEMENTED, THE NEXT
NUMBER COULD BE PROCESSED IN EXECUTION UNITS A
AND B WHILE C WAS BEING PERFORMED.

PIPELINING
• TO GET A ROUGH INDICATION OF PERFORMANCE
INCREASE THROUGH PIPELINE, THE STAGE EXECUTION
INTERVAL MAY BE TAKEN TO BE THE EXECUTION TIME
OF THE SLOWEST PIPELINE STAGE.
• THE PERFORMANCE INCREASE FROM PIPELINING IS
ROUGHLY EQUAL TO THE SUM OF THE AVERAGE
EXECUTION TIMES FOR ALL STAGES OF THE PIPELINE,
DIVIDED BY THE AVERAGE VALUE OF THE EXECUTION
TIME OF THE SLOWEST PIPELINE STAGE FOR THE INST
MIX CONSIDERED.

PIPELINING
• NON-SEQUENTIAL INSTS CAUSE THE
INSTRUCTIONS BEHIND IN THE PIPELINE TO BE
EMPTIED AND FILLING TO BE RESTARTED.
• NON-SEQUENTIAL INSTS. TYPICALLY COMPRISE
15 TO 30% OF INSTRUCTIONS AND THEY REDUCE
PIPELINE PERFORMANCE BY A GREATER
PERCENTAGE THAN THEIR PROBABILITY OF
OCCURRENCE.

CACHE MEMORY
• VON-NEUMANN SYSTEM PERFORMANCE IS
CONSIDERABLY EFFECTED BY MEMORY ACCESS TIME
AND MEMORY BW (MAXIMUM MEMORY TRANSFER
RATE).
• THESE LIMITATIONS ARE SPECIALLY TIGHT FOR 32 BIT
PROCESSORS WITH HIGH CLOCK SPEEDS.
• WHILE STATIC RAM WITH 25ns ACCESS TIMES ARE
CAPABLE OF KEEPING PACE WITH PROC SPEED, THEY
MUST BE LOCATED ON THE SAME BOARD TO MINIMISE
DELAYS, THUS LIMITING THE AMOUNT OF HIGH SPEED
MEMORY AVAILABLE.

CACHE MEMORY
• DRAM HAS A GREATER CAPACITY PER CHIP AND
A LOWER COST, BUT EVEN THE FASTEST DRAM
CAN’T KEEP PACE WITH THE PROCESSOR,
PARTICULARLY WHEN IT IS LOCATED ON A
SEPARATE BOARD ATTACHED TO A MEMORY
BUS.
• WHEN A PROC REQUIRES INST/DATA FROM/TO
MEMORY, IT ENTERS A WAIT STATE UNTIL IT IS
AVAILABLE. THIS REDUCES PROCESSORS
PERFORMANCE.

CACHE MEMORY
• CACHE ACTS AS A FAST LOCAL STORAGE
BUFFER BETWEEN THE PROC AND THE MAIN
MEMORY.
• OFF-CHIP BUT ON-BOARD CACHE MAY REQUIRE
SEVERAL MEMORY CYCLES WHEREAS ON-CHIP
CACHE MAY ONLY REQUIRE ONE MEMORY
CYCLE, BUT ON-BOARD CACHE CAN PREVENT
THE EXCESSIVE NO. OF WAIT STATES IMPOSED
BY MEMORY ON THE SYSTEM BUS AND IT
REDUCES THE SYSTEM BUS LOAD.

CACHE MEMORY
• THE COST OF IMPLEMENTING AN ON-BOARD
CACHE IS MUCH LOWER THAN THE COST OF
FASTER SYSTEM MEMORY REQUIRED TO
ACHIEVE THE SAME MEMORY PERFORMANCE.
• CACHE PERFORMANCE DEPENDS ON ACCESS
TIME AND HIT RATIO, WHICH IS DEPENDENT ON
THE SIZE OF THE CACHE AND THE NO. OF BYTES
BROUGHT INTO CACHE ON ANY FETCH FROM
THE MAIN MEMORY (THE LINE SIZE).

CACHE MEMORY
• INCREASING THE LINE SIZE INCREASES THE
CHANCE THAT THERE WILL BE A CACHE HIT ON
THE NEXT MEMORY REFERENCE.
• IF A 4K BYTE CACHE WITH A 4 BYTE LINE SIZE
HAS A HIT RATIO OF 80%, DOUBLING THE LINE
SIZE MIGHT INCREASE THE HIT RATIO TO 85%
BUT DOUBLING THE LINE SIZE AGAIN MIGHT
ONLY INCREASE THE HIT RATIO TO 87%.

CACHE MEMORY
• OVERALL MEMORY PERFORMANCE IS A
FUNCTION OF CACHE ACCESS TIME, CACHE HIT
RATIO AND MAIN MEMORY ACCESS TIME FOR
CACHE MISSES.
• A SYSTEM WITH 80% CACHE HIT RATIO AND 120ns
CACHE ACCESS TIME ACCESSES MAIN MEMORY
20% OF THE TIME WITH AN ACCESS TIME OF 600
ns. THE AV ACCESS TIME IN ns WILL BE (0.8x120)
+[0.2x(600 + 120)]= 240

CACHE DESIGN
• PROCESSORS WITH DEMAND PAGED VIRTUAL
MEMORY SYSTEMS REQUIRE AN ASSOCIATIVE
CACHE.
• VIRTUAL MEM SYSTEMS ORGANIZE ADDRESSES
BY THE START ADDRESSES FOR EACH PAGE AND
AN OFFSET WHICH LOCATES THE DATA WITHIN
THE PAGE.
• AN ASSOCIATIVE CACHE ASSOCIATES THE
OFFSET WITH THE PAGE ADDRESS TO FIND THE
DATA NEEDED.

CACHE DESIGN
• WHEN ACCESSED, THE CACHE CHECKS TO SEE IF IT
CONTAINS THE PAGE ADDRESS (OR TAG FIELD); IF SO,
IT ADDS THE OFFSET AND, IF A CACHE HIT IS
DETECTED, THE DATA IS FETCHED IMMEDIATELY
FROM THE CACHE.
• PROBLEMS CAN OCCUR IN A SINGLE SET-ASSOCIATIVE
CACHE IF WORDS WITHIN DIFFERENT PAGES HAVE THE
SAME OFFSET.
• TO MINIMISE THIS PROBLEM A 2-WAY SET-
ASSOCIATIVE CACHE IS USED. THIS IS ABLE TO
ASSOCIATE MORE THAN ONE SET OF TAGS AT A TIME
ALLOWING THE CACHE TO STORE THE SAME OFFSET
FROM TWO DIFFERENT PAGES.

CACHE DESIGN
• A FULLY ASSOCIATIVE CACHE ALLOWS ANY
NUMBER OF PAGES TO USE THE CACHE
SIMULTANEOUSLY.
• A CACHE REQUIRES A REPLACEMENT
ALGORITHM TO FIND REPLACEMENT CACHE
LINES WHEN A MISS OCCURS.
• PROCESSORS THAT DO NOT USE DEMAND PAGED
VIRTUAL MEMORY, CAN EMPLOY A DIRECT
MAPPED CACHE WHICH CORRESPONDS EXACTLY
TO THE PAGE SIZE AND ALLOWS DATA FROM
ONLY ONE PAGE TO BE STORED AT A TIME.

MEMORY ARCHITECTURES
• 32 BIT PROCESSORS HAVE INTRODUCED 3 NEW
CONCEPTS IN THE WAY THE MEMORY IS
INTERFACED:
1. LOCAL MEMORY BUS EXTENSIONS
2. MEMORY INTEREAVING
3. VIRTUAL MEMORY MANAGEMENT

LOCAL MEM BUS EXTENSIONS
• IT PERMITS LARGER LOCAL MEMORIES TO BE
CONNECTED WITHOUT THE DELAYS CAUSED BY BUS
REQUESTS AND BUS ARBITRATION FOUND ON
MULTIPROCESSOR BUSES.
• IT HAS BEEN PROVIDED TO INCREASE THE SIZE OF THE
LOCAL MEMORY ABOVE THAT WHICH CAN BE
ACCOMODATED ON THE PROCESSOR BOARD.
• BY OVERLAPPING THE LOCAL MEM BUS AND THE
SYSTEM BUS CYCLES IT IS POSSIBLE TO ACHIEVE
HIGHER MEM ACCESS RATES FROM PROCESSORS WITH
PIPELINES WHICH PERMIT THE ADDRESS OF THE NEXT
MEMORY REFERENCE TO BE GENERATED WHILE THE
PREVIOUS DATA WORD IS BEING FETCHED.

MEMORY INTERLEAVING
• PIPELINED PROCESSORS WITH THE ABILITY TO
GENERATE THE ADDRESS OF THE NEXT MEMORY
REFERENCE WHILE FETCHING THE PREVIOUS
DATA WORD WOULD BE SLOWED DOWN IF THE
MEMORY WERE UNABLE TO BEGIN THE NEXT
MEMORY ACCESS UNTIL THE PREVIOUS MEM
CYCLE HAD BEEN COMPLETED.
• THE SOLUTION IS TO USE TWO-WAY MEMORY
INTERLEAVING. IT USES 2 MEM BOARDS- 1 FOR
ODD ADDRESSES AND 1 FOR EVEN ADDRESSES.

MEMORY INTERLEAVING
• ONE BOARD CAN BEGIN THE NEXT MEM CYCLE
WHILE THE OTHER BOARD COMPLETES THE
PREVIOUS CYCLE.
• THE SPEED ADV IS GREATEST WHEN MULTIPLE
SEQUENTIAL MEM ACCESSES ARE REQUIRED FOR
BURST I/O TRANSFERS BY DMA.
• DMA DEFINES A BLOCK TRANSFER IN TERMS OF
A STARTING ADDRESS AND A WORD COUNT FOR
SEQUENTIAL MEM ACCESSES.

MEMORY INTERLEAVING
• TWO WAY INTERLEAVING MAY NOT PREVENT
MEM WAIT STATES FOR SOME FAST SIGNAL
PROCESSING APPLICATIONS AND SYSTEMS HAVE
BEEN DESIGNED WITH 4 OR MORE WAY
INTERLEAVING IN WHICH THE MEM BOARDS ARE
ASSIGNED CONSECUTIVE ADDRESSES BY A
MEMORY CONTROLLER.

• EVEN WITH THESE ENHANCEMENTS, THE SEQUENTIAL
VON NEUMANN ARCHITECTURE REACHED THE LIMITS
IN PROCESSING SPEED BECAUSE THE SEQUENTIAL
FETCHING OF INSTS AND DATA THROUGH A COMMON
MEMORY INTERFACE FORMED THE BOTTLENECK.
• THUS, PARALLEL PROC ARCHITECTURES CAME INTO
BEING WHICH PERMIT LARGE NUMBER OF COMPUTING
ELEMENTS TO BE PROGRAMMED TO WORK TOGETHER
SIMULTANEOUSLY. THE USEFULNESS OF PARALLEL
PROCESSOR DEPENDS UPON THE AVAILABILITY OF
SUITABLE PARALLEL ALGORITHMS.

HOW TO INCREASE THE SYSTEM SPEED?
1. USING FASTER COMPONENTS. COSTS MORE,
DISSIPATE CONSIDERABLE HEAT.
THE RATE OF GROWTH OF SPEED USING
BETTER TECHNOLOGY IS VERY SLOW. eg., IN
80’S BASIC CLOCK RATE WAS 50 MHz AND
TODAY IT IS AROUND 2 GHz, DURING THIS
PERIOD SPEED OF COMPUTER IN SOLVING
INTENSIVE PROBLEMS HAS GONE UP BY A
FACTOR OF 100,000. IT IS DUE TO THE
INCREASED ARCHITECTURE.

HOW TO INCREASE THE SYSTEM SPEED?
2. ARCHITECTURAL METHODS:
A. USE PARALLELISM IN SINGLE PROCESSOR
[ OVERLAPPING EXECUTION OF NO OF INSTS
(PIPELINING)]
B. OVERLAPPING OPERATION OF DIFFERENT
UNITS
C. INCREASE SPEED OF ALU BY EXPLOITING
DATA/TEMPORAL PARALLELISM
D. USING NO OF INTERCONNECTED PROCESSORS
TO WORK TOGETHER

PARALLEL COMPUTERS
• THE IDEA EMERGED AT CIT IN 1981
• A GROUP HEADED BY CHARLES SEITZ AND
GEOFFREY FOX BUILT A PARALLEL COMPUTER
IN 1982
• 16 NOS 8085 WERE CONNECTED IN A HYPERCUBE
CONFIGURATION
• ADV WAS LOW COST PER MEGAFLOP

PARALLEL COMPUTERS
• BESIDES HIGHER SPEED, OTHER FEATURES OF
PARALLEL COMPUTERS ARE:
 BETTER SOLUTION QUALITY: WHEN ARITHMETIC
OPS ARE DISTRIBUTED, EACH PE DOES SMALLER
NO OF OPS, THUS ROUNDING ERRORS ARE
REDUCED
 BETTER ALGORITHMS
 BETTER AND FASTER STORAGE
 GREATER RELIABILITY

CLASSIFICATION OF COMPUTER
ARCHITECTURE
• FLYNN’S TAXONOMY: IT IS BASED
UPON HOW THE COMPUTER
RELATES ITS INSTRUCTIONS TO THE
DATA BEING PROCESSED –
SISD
SIMD
MISD
MIMD

FLYNN’S TAXONOMY
• SISD: CONVENTIONAL VON-NEUMANN SYSTEM.
CONTROL
UNIT
PROCESSOR
INST STREAM
DATA
STREAM

FLYNN’S TAXONOMY
• SIMD: IT HAS A SINGLE STREAM OF VECTOR
INSTS THAT INITIATE MANY OPERATIONS. EACH
ELEMENT OF A VECTOR IS REGARDED AS A
MEMBER OF A SEPARATE DATA STREAM GIVING
MULTIPLE DATA STREAMS.
CONTROL
UNIT
INST
STREAM
PROCESSOR
PROCESSOR
PROCESSOR
DATA STREAM 1
DATA STREAM 2
DATA STREAM 3SYNCHRONOUS
MULTIPROCESSOR

FLYNN’S TAXONOMY
• MISD: NOT POSSIBLE
C U 1
C U 2
PU 3
PU 2
C U 3
PU 1
INST STREAM 1
INST STREAM 2
INST STREAM 3
DS

FLYNN’S TAXONOMY
• MIMD: MULTIPROCESSOR CONFIGURATION AND
ARRAY OF PROCESSORS.
CU 1
CU 2
CU 3
IS 1
IS 2
IS 3
DS 1
DS 2
DS 3

FLYNN’S TAXONOMY
• MIMD COMPUTERS COMPRISE OF INDEPENDENT
COMPUTERS, EACH WITH ITS OWN MEMORY,
CAPABLE OF PERFORMING SEVERAL
OPERATIONS SIMULTANEOUSLY.
• MIMD COMPS MAY COMPRISE OF A NUMBER OF
SLAVE PROCESSORS WHICH MAY BE
INDIVIUALLY CONNECTED TO MULTI-ACCESS
GLOBAL MEMORY BY A SWITCHING MATRIX
UNDER THE CONTROL OF MASTER PROCESSOR.

FLYNN’S TAXONOMY
• THIS CLASSIFICATION IS TOO BROAD.
• IT PUTS EVERYTHING EXCEPT
MULTIPROCESSORS IN ONE CLASS.
• IT DOES NOT REFLECT THE CONCURRENCY
AVAILABLE THROUGH THE PIPELINE
PROCESSING AND THUS PUTS VECTOR
COMPUTERS IN SISD CLASS.

SHORE’S CLASSIFICATION
• SHORE CLASSIFIED THE COMPUTERS ON THE BASIS
OF ORGANIZATION OF THE CONSTITUENT ELEMENTS
OF THE COMPUTER.
• SIX DIFFERENT KINDS OF MACHINES WERE
RECOGNIZED:
1. CONVENTIONAL VON NEWMANN ARCHITECTURE
WITH 1 CU, 1 PU, IM AND DM. A SINGLE DM READ
PRODUCES ALL BITS FOR PROCESSING BY PU. THE PU
MAY CONTAIN MULTIPLE FUNCTIONAL UNITS WHICH
MAY OR MAY NOT BE PIPELINED. SO, IT INCLUDES
BOTH THE SCALAR COMPS (IBM 360/91, CDC7600)AND
PIPELINED VECTOR COMPUTERS (CRAY 1, CYBER 205)

• TYPE I:
IM CU
HORIZONTAL PU
WORD SLICE DM
NOTE THAT THE PROCESSING
IS CHARACTERISED AS
HORIZONTAL (NO OF BITS IN
PARALLEL AS A WORD)

• MACHINE 2: SAME AS MACHINE 1 EXCEPT THAT
SM FETCHES A BIT SLICE FROM ALL THE WORDS
IN THE MEMORY AND PU IS ORGANIZED TO
PERFORM THE OPERATIONS IN A BIT SERIAL
MANNER ON ALL THE WORDS.
• IF THE MEMORY IS REGARDED AS A 2D ARRAY
OF BITS WITH ONE WORD STORED PER ROW,
THEN THE MACHINE 2 READS VERTICAL SLICE
OF BITS AND PROCESSES THE SAME, WHEREAS
THE MACHINE 1 READS AND PROCESSES
HORIZONTAL SLICE OF BITS. EX. MPP, ICL DAP

• MACHINE 2:
IM
CU
VERTICAL
PU
BIT SLICE
DM

• MACHINE 3: COMBINATION OF 1 AND 2.
• IT COULD BE CHARACTERISED HAVING A
MEMORY AS AN ARRAY OF BITS WITH BOTH
HORIZONTAL AND VERTICAL READING AND
PROCESSING POSSIBLE.
• SO, IT WILL HAVE BOTH VERTICAL AND
HORIZONTAL PROCESSING UNITS.
• EXAMPLE IS OMENN 60 (1973)

• MACHINE 3:
IM
CU
VERTICA
L PU
HORIZON
TAL PU
DM

• MACHINE 4: IT IS OBTAINED BY REPLICATING THE PU
AND DM OF MACHINE 1.
• AN ENSEMBLE OF PU AND DM IS CALLED PROCESSING
ELEMENT (PE).
• THE INSTS ARE ISSUED TO THE PEs BY A SINGLE CU. PEs
COMMUNICATE ONLY THROUGH CU.
• ABSENCE OF COMM BETWEEN PEs LIMITS ITS
APPLICABILITY
• EX: PEPE(1976)

• MACHINE 4:
IM
CU
PU PU PU
DM DM DM

• MACHINE 5: SIMILAR TO MACHINE 4 WITH THE
ADDITION OF COMMUNICATION BETWEEN
PE.EXAMPLE: ILLIAC IV
IM
CU
PU PU PU
DM DM DM

• MACHINE 6:
• MACHINES 1 TO 5 MAINTAIN SEPARATION
BETWEEN DM AND PU WITH SOME DATA BUS OR
CONNECTION UNIT PROVIDING THE
COMMUNICATION BETWEEN THEM.
• MACHINE 6 INCLUDES THE LOGIC IN MEMORY
ITSELF AND IS CALLED ASSOCIATIVE
PROCESSOR.
• MACHINES BASED ON SUCH ARCHITECTURES
SPAN A RANGE FROM SIMPLE ASSOCIATIVE
MEMORIES TO COMPLEX ASSOCIATIVE PROCS.

• MACHINE 6:
IM
CU
PU + DM

FENG’S CLASSIFICATION
• FENG PROPOSED A SCHEME ON THE BASIS OF
DEGREE OF PARALLELISM TO CLASSIFY
COMPUTER ARCHITECTURE.
• MAXIMUM NO OF BITS THAT CAN BE PROCESSED
EVERY UNIT OF TIME BY THE SYSTEM IS CALLED
“MAXIMUM DEGREE OF PARALLELISM”

FENG’S CLASSIFICATION
• BASED ON FENG’S SCHEME, WE HAVE
SEQUENTIAL AND PARALLEL OPERATIONS AT
BIT AND WORD LEVELS TO PRODUCE THE
FOLLOWING CLASSIFICATION:
 WSBS NO CONCEIVABLE IMPLEMENTATION
 WPBS STARAN
 WSBP CONVENTIONAL COMPUTERS
 WPBP ILLIAC IV
o THE MAX DEGREE OF PARALLELISM IS GIVEN BY
THE PRODUCT OF THE NO OF BITS IN THE WORD
AND NO OF WORDS PROCESSED IN PARALLEL

HANDLER’S CLASSIFICATION
• FENG’S SCHEME, WHILE INDICATING THE
DEGREE OF PARALLELISM DOES NOT ACCOUNT
FOR THE CONCURRENCY HANDLED BY THE
PIPELINED DESIGNS.
• HANDLER’S SCHEME ALLOWS THE PIPELINING
TO BE SPECIFIED.
• IT ALLOWS THE IDENTIFICATION OF
PARALLELISM AND DEGREE OF PIPELINING
BUILT IN THE HARDWARE STRUCTURE

HANDLER’S CLASSIFICATION
• HANDLER DEFINED SOME OF THE TERMS AS:
• PCU – PROCESSOR CONTROL UNITS
• ALU – ARITHMETIC LOGIC UNIT
• BLC – BIT LEVEL CIRCUITS
• PE – PROCESSING ELEMENTS
• A COMPUTING SYSTEM C CAN THEN BE CHARATERISED
BY A TRIPLE AS T(C) = (KxK', DxD', WxW')
• WHERE K=NO OF PCU, K'= NO OF PROCESSORS THAT
ARE PIPELINED, D=NO OF ALU,D'= NO OF PIPELINED
ALU, W=WORDLENGTH OF ALU OR PE AND W'= NO OF
PIPELINE STAGES IN ALU OR PE

COMPUTER PROGRAM ORGANIZATION
• BROADLY, THEY MAY BE CLASSIFIED AS:
CONTROL FLOW PROGRAM
ORGANIZATION
DATAFLOW PROGRAM ORGANIZATION
REDUCTION PROGRAM ORGANIATION

• IT USES EXPLICIT FLOWS OF CONTROL INFO TO
CAUSE THE EXECUTION OF INSTS.
• DATAFLOW COMPS USE THE AVAILABILITY OF
OPERANDS TO TRIGGER THE EXECUTION OF
OPERATIONS.
• REDUCTION COMPUTERS USE THE NEED FOR A
RESULT TO TRIGGER THE OPERATION WHICH
WILL GENERATE THE REQUIRED RESULT.

• THE THREE BASIC FORMS OF COMP PROGRAM
ORGANIZATION MAY BE DESCRIBED IN TERMS
OF THEIR DATA MECHANISM (WHICH DEFINES
THE WAY A PERTICULAR ARGUMENT IS USED BY
A NUMBER OF INSTRUCTIONS) AND THE
CONTROL MECHANISM (WHICH DEFINES HOW
ONE INST CAUSES THE EXECUTION OF ONE OR
MORE OTHER INSTS AND THE RESULTING
CONTROL PATTERN).

• CONTROL FLOW PROCESSORS HAVE A “BY
REFERENCE” DATA MECHANISM (WHICH USES
REFERENCES EMBEDDED IN THE INSTS BEING
EXECUTED TO ACCESS THE CONTENTS OF THE
SHARED MEMORY) AND TYPICALLY A
‘SEQUENTIAL’ CONTROL MECHANISM ( WHICH
PASSES A SINGLE THREAD OF CONTROL FROM
INSTRUCTION TO INSTRUCTION).

• DATAFLOW COMPUTERS HAVE A “BY VALUE”
DATA MECHANISM (WHICH GENERATES AN
ARGUMENT AT RUN-TIME WHICH IS REPLICATED
AND GIVEN TO EACH ACCESSING INSTRUCTION
FOR STORAGE AS A VALUE) AND A ‘PARALLEL’
CONTROL MECHANISM.
• BOTH MECHANISMS ARE SUPPORTED BY DATA
TOKENS WHICH CONVEY DATA FROM PRODUCER
TO CONSUMER INSTRUCTIONS AND CONTRIBUTE
TO THE ACTIVATION OF CONSUMER INSTS.

• TWO BASIC TYPES OF REDUCTION PROGRAM
ORGANIZATIONS HAVE BEEN DEVELOPED:
A. STRING REDUCTION WHICH HAS A ‘BY VALUE’
DATA MECHANISM AND HAS ADVANTAGES
WHEN MANIPULATING SIMPLE EXPRESSIONS.
B. GRAPH REDUCTION WHICH HAS A ‘BY
REFERENCE’ DATA MECHANISM AND HAS
ADVANTAGES WHEN LARGER STRUCTURES
ARE INVOLVED.

• CONTROL-FLOW AND DATA-FLOW PROGRAMS
ARE BUILT FROM FIXED SIZE PRIMITIVE INSTS
WITH HIGHER LEVEL PROGRAMS CONSTRUCTED
FROM SEQUENCES OF THESE PRIMITIVE
INSTRUCTIONS AND CONTROL OPERATIONS.
• REDUCTION PROGRAMS ARE BUILT FROM HIGH
LEVEL PROGRAM STRUCTURES WITHOUT THE
NEED FOR CONTROL OPERATORS.

• THE RELATIONSHIP OF THEDATA AND CONTROL
MECHANISMS TO THE BASIC COMPUTER
PROGRAM ORGANIZATIONS CAN BE SHOWN AS
UNDER:
DATA MECHANISM
BY VALUE BY REFERENCE
CONTROL MECHANISM
SEQUENTIAL VON-NEUMANN CON.FLOW
PARALLEL DATA FLOW PARALLEL CONTROL FLOW
RECURSIVE STRING REDUCTION GRAPH REDUCTION

MACHINE ORGANIZATION
• MACHINE ORGANIZATION CAN BE CLASSIFIED
AS FOLLOWS:
 CENTRALIZED: CONSISTING OF A SINGLE
PROCESSOR, COMM PATH AND MEMORY. A
SINGLE ACTIVE INST PASSES EXECUTION TO A
SPECIFIC SUCCESSOR INSTRUCTION.
o TRADITIONAL VON-NEUMANN PROCESSORS
HAVE CENTRALIZED MACHINE ORGANIZATION
AND A CONTROL FLOW PROGRAM
ORGANIZATION.

 PACKET COMMUNICATION: USING A CIRCULAR
INST EXECUTION PIPELINE IN WHICH
PROCESSORS, COMMUNICATIONS AND
MEMORIES ARE LINKED BY POOLS OF WORK.
o NEC 7281 HAS A PACKET COMMUNICATION
MACHINE ORGANIZATION AND DATAFLOW
PROGRAM ORGANIZATION.

• EXPRESSION MANIPULATION WHICH USES IDENTICAL
RESOURCES IN A REGULAR STRUCTURE, EACH
RESOURCE CONTAINING A PROCESSOR,
COMMUNICATION AND MEMORY. THE PROGRAM
CONSISTS OF ONE LARGE STRUCTURE, PARTS OF
WHICH ARE ACTIVE WHILE OTHER PARTS ARE
TEMPORARILY SUSPENDED.
• AN EXPRESSION MANIPULATION MACHINE MAY BE
CONSTRUCTED FROM A REGULAR STRUCTURE OF T414
TRANSPUTERS, EACH CONTAINING A VON-NEUMANN
PROCESSOR, MEMORY AND COMMUNICATION LINKS.

MULTIPROCESSING SYSTEMS
• IT MAKES USE OF SEVERAL PROCESSORS, EACH
OBEYING ITS OWN INSTS, USUALLY
COMMUNICATING VIA A COMMON MEMORY.
• ONE WAY OF CLASSIFYING THESE SYSTEMS IS
BY THEIR DEGREE OF COUPLING.
• TIGHTLY COUPLED SYSTEMS HAVE PROCESSORS
INTERCONNECTED BY A MULTIPROCESSOR
SYSTEM BUS WHICH BECOMES A PERFORMANCE
BOTTLENECK.

• INTERCONNECTION BY A SHARED MEMORY IS LESS
TIGHTLY COUPLED AND A MULTIPORT MEMORY MAY
BE USED TO REDUCE THE BUS BOTTLENECK.
• THE USE OF SEVERAL AUTONOMOUS SYSTEMS, EACH
WITH ITS OWN OS, IN A CLUSTER IS MORE LOOSELY
COUPLED.
• THE USE OF NETWORK TO INTERCONNECT SYSTEMS,
USING COMM SOFTWARE, IS THE MOST LOOSELY
COUPLED ALTERNATIVE.

• DEGREE OF COUPLING:
NETWORK
SW
NETWORK
SW
NETWORK LINK
OS OSCLUSTER LINK
SYSTEM
MEMORY
SYSTEM
MEMORY
SYSTEM BUS
CPU CPUMULTIPROCESSOR BUS

• MULTIPROCESSORS MAY ALSO BE CLASSIFIED
AS AUTOCRATIC OR EGALITARIAN.
• AUTOCRATIC CONTROL IS SHOWN WHERE A
MASTER-SLAVE RELATIONSHIP EXISTS BETWEEN
THE PROCESSORS.
• EGALITARIAN CONTROL GIVES ALL PROCESSORS
EQUAL CONTROL OF SHARED BUS ACCESS.

• MULTIPROCESSING SYSTEMS WITH SEPARATE
PROCESSORS AND MEMORIES MAY BE
CLASSIFIED AS ‘DANCE HALL’ CONFIGURATIONS
IN WHICH THE PROCESSORS ARE LINED UP ON
ONE SIDE WITH THE MEMORIES FACING THEM.
• CROSS CONNECTIONS ARE MADE BY A
SWITCHING NETWORK.

• DANCE HALL CONFIGURATION:
CPU 1
CPU 2
CPU 3
CPU 4
SWITCHI
NG
NETWO
RK
MEM 1
MEM 2
MEM 3
MEM 4

• ANOTHER CONFIGURATION IS ‘BOUDOIR CONFIG’ IN WHICH EACH
PROCESSOR IS CLOSELY COUPLED WITHITS OWN MEMORY AND A
NETWORK OF SWITCHES IS USED TO LINK THE PROCESSOR-MEMORY
PAIRS.
CPU 1
MEM 1
CPU 2
MEM 2
CPU 3
MEM 3
CPU 4
MEM 4
SWITCHING
NETWORK

• ANOTHER TERM, WHICH IS USED TO DESCRIBE A
FORM OF PARALLEL COMPUTING IS
CONCURRENCY.
• IT DENOTES INDEPENDENT, AYNCHRONOUS
OPERATION OF A COLLECTION OF PARALLEL
COMPUTING DEVICES RATHER THAN THE
SYNCHRONOUS OPERATION OF DEVICES IN A
MULTIPROCESSOR SYSTEM.

SYSTOLIC ARRAYS
• IT MAY BE TERMED AS MISD SYSTEM.
• IT IS A REGULAR ARRAY OF PROCESSING ELEMENTS,
EACH COMMUNICATING WITH ITS NEAREST
NEIGHBOURS AND OPERATING SYNCHRONOUSLY
UNDER THE CONTROL OF A COMMON CLOCK WITH A
RATE LIMITED BY THE SLOWEST PROCESSOR IN THE
ARRAY.
• THE ERM SYSTOLIC IS DERIVED FROM THR RHYTHMIC
CONTRACTION OF THE HEART, ANALOGOUS TO THE
RHYTHMIC PUMPING OF DATA THROUGH AN ARRAY OF
PROCESSING ELEMENTS.

WAVEFRONT ARRAY
• IT IS A REGULAR ARRAY OF PROCESSING ELEMENTS,
EACH COMMUNICATING WITH ITS NEAREST
NEIGHBOURS BUT OPERATING WITH NO GLOBAL
CLOCK.
• IT EXHIBITS CONCURRENCY AND IS DATA DRIVEN.
• THE OPERATION OF EACH PROCESSOR IS CONTROLLED
LOCALLY AND IS ACTIVATED BY THE ARRIVAL OF DATA
AFTER ITS PREVIOUS OUTPUT HAS BEEN DELIVERED TO
THE APPROPRIATE NEIGHBOURING PROCESSOR.

WAVEFRONT ARRAY
• PROCESSING WAVEFRONTS DEVELOP ACROSS
THE ARRAY AS PROCESSORS PASS ON THE
OUTPUT DATA TO THEIR NEIGHBOUR. HENCE
THE NAME.

GRANULARITY OF PARALLELISM
• PARALLEL PROCESSING EMPHASIZES THE USE OF
SEVERAL PROCESSING ELEMENTS WITH THE
MAIN OBJECTIVE OF GAINING SPEED IN
CARRYING OUT A TIME CONSUMING COMPUTING
JOB
• A MULTI-TASKING OS EXECUTES JOB
CONCURRENTLY BUT THE OBJECTIVE IS TO
EFFECT THE CONTINUED PROGRESS OF ALL THE
TASKS BY SHARING THE RESOURCES IN AN
ORDERLY MANNER.

• THE PARALLEL PROCESSING EMPHASIZES THE
EXPLOITATION OF CONCURRENCY AVAILABLE
IN A PROBLEM FOR CARRYING OUT THE
COMPUTATION BY EMPLOYING MORE THAN ONE
PROCESSOR TO ACHIEVE BETTER SPEED AND/OR
THROUGHPUT.
• THE CONCURRENCY IN THE COMPUTING
PROCESS COULD BE LOOKED UPON FOR
PARALLEL PROCESSING AT VARIOUS LEVELS
(GRANULARITY OF PARALLELISM) IN THE
SYSTEM.

• THE FOLLOWING GRANULARITIES OF PARALLELISM
MAY BE IDENTIFIED IN ANY EXISTING SYSTEM:
o PROGRAM LEVEL PARALLELISM
o PROCESS OR TASK LEVEL PARALLELISM
o PARALLELISM AT THE LEVEL OF GROUP OF
STATEMENTS
o STATEMENT LEVEL PARALLELISM
o PARALLELISM WITHIN A STATEMENT
o INSTRUCTION LEVEL PARALLELISM
o PARALLELISM WITHIN AN INSTRUCTION
o LOGIC AND CIRCUIT LEVEL PARALLELISM

• THE GRANULARITIES ARE LISTED IN THE
INCREASING DEGREE OF FINENESS.
• GRANULARITIES AT LEVELS 1,2 AND 3 CAN BE
EASILY IMPLEMENTED ON A CONVENTIONAL
MULTIPROCESSOR SYSTEM.
• MOST MULTI-TASKING OS ALLOW CREATION
AND SCHEDULING OF PROCESSES ON THE
AVAILABLE RESOURCES.

• SINCE A PROCESS REPRESENTS A SIZABLE CODE IN
TERMS OF EXECUTION TIME, THE OVERLOADS IN
EXPLOITING THE PARALLELISM AT THESE
GRANULARITIES ARE NOT EXCESSIVE.
• IF THE SAME PRINCIPLE IS APPLIED TO THE NEXT FEW
LEVELS, INCREASED SCHEDULING OVERHEADS MAY
NOT WARRANT PARALLEL EXECUTION
• IT IS SO BECAUSE THE UNIT OF WORK OF A MULTI-
PROCESSOR IS CURRENTLY MODELLED AT THE LEVEL
OF A PROCESS OR TASK AND IS REASONABLY
SUPPORTED ON THE CURRENT ARCHITECTURES.

• THE LAST THREE LEVELS ARE BEST HANDLED BY
HARDWARE. SEVERAL MACHINES HAVE BEEN BUILT TO
PROVIDE THE FINE GRAIN PARALLELISM IN VARYING
DEGREES.
• A MACHINE HAVING INST LEVEL PARALLELISM
EXECUTES SEVERAL INSTS SIMULTANEOUSLY.
EXAMPLES ARE PIPELINE INST PROCESSORS,
SYNCHRONOUS ARRAY PROCESSORS, ETC.
• CIRCUIT LEVEL PARALLELISM EXISTS IN MOST
MACHINES IN THE FORM OF PROCESSING MULTIPLE
BITS/BYTES SIMULTANEOUSLY.

PARALLEL ARCHITECTURES
• THERE ARE NUMEROUS ARCHITECTURES THAT HAVE
BEEN USED IN THE DESIGN OF HIGH SPEED COMPUTERS.
IT FALLS BASICALLY INTO 2 CLASSES:
 GENERAL PURPOSE &
 SPECIAL PURPOSE
o GENERAL PURPOSE ARCHITECTURES ARE DESIGNED TO
PROVIDE THE RATED SPEEDS AND OTHER COMPUTING
REQUIREMENTS FOR VARIETY OF PROBLEMS WITH
SAME PERFORMANCE.

• THE IMPORTANT ARCHITECTURAL IDEAS BEING
USED IN DESIGNING GEN PURPOSE HIGH SPEED
COMPUTERS ARE:
 PIPELINED ARCHITECTURES
 ASYNCHRONOUS MULTI-PROCESSORS
 DATA-FLOW COMPUTERS

• THE SPECIAL PURPOSE MACHINES HAVE TO EXCEL FOR
WHAT THEY HAVE BEEN DESIGNED. IT MAY OR MAY
NOT DO SO FOR OTHER APPLICATIONS. SOME OF THE
IMPORTANT ARCHITECTURAL IDEAS FOR DEDICATED
COMPUTERS ARE:
 SYNCHRONOUS MULTI-PROCESSORS(ARRAY
PROCESSOR)
 SYSTOLIC ARRAYS
 NEURAL NETWORKS

ARRAY PROCESSORS
• IT CONSISTS OF SEVERAL PE, ALL OF WHICH EXECUTE
THE SAME INST ON DIFFERENT DATA.
• THE INSTS ARE FETCHED AND BROADCAST TO ALL THE
PE BY A COMMON CU.
• THE PE EXECUTE INSTS ON DATA RESIDING IN THEIR
OWN MEMORY.
• THE PE ARE LINKED VIA AN INTERCONNECTION
NETWORK TO CARRY OUT DATA COMMUNICATION
BETWEEN THEM.

ARRAY PROCESSORS
• THERE ARE SEVERAL WAYS OF CONNECTING PE
• THESE MACHINES REQUIRE SPECIAL
PROGRAMMING EFFORTS TO ACHIEVE THE
SPEED ADVANTAGE
• THE COMPUTATIONS ARE CARRIED OUT
SYNCHRONOUSLY BY THE HW AND THEREFORE
SYNC IS NOT AN EXPLICIT PROBLEM

ARRAY PROCESSORS
• USING AN INTERCONNECTION NETWORK:
PE1 PE2 PE3 PE4 PEn
CU AND
SCALAR
PROCESS
OR
INTERCONNECTION
NETWORK

ARRAY PROCESSORS
• USING AN ALIGNMENT NETWORK:
PE0 PE1 PE2 PEn
ALIGNMENT NETWORK
MEM O MEM1 MEM2 MEMK
CONTROL
UNIT AND
SCALAR
PROCESSOR

CONVENTIONAL MULTI-PROCESSORS
• ASYNCHRONOUS MULTIPROCESSORS
• BASED ON MULTIPLE CPUs AND MEM BANKS
CONNECTED THROUGH EITHER A BUS OR
CONNECTION NETWORK IS A COMMONLY USED
TECHNIQUE TO PROVIDE INCREASED
THROUGHPUT AND/OR RESPONSE TIME IN A
GENERAL PURPOSE COMPUTING ENVIRONMENT.

• IN SUCH SYSTEMS, EACH CPU OPERATES
INDEPENDENTLY ON THE QUANTUM OF WORK GIVEN
TO IT
• IT HAS BEEN HIGHLY SUCCESSFUL IN PROVIDING
INCREASED THROUGHPUT AND/OR RESPONSE TIME IN
TIME SHARED SYSTEMS.
• EFFECTIVE REDUCTION OF THE EXECUTION TIME OF A
GIVEN JOB REQUIRES THE JOB TO BE BROKEN INTO
SUB-JOBS THAT ARE TO BE HANDLED SEPARATELY BY
THE AVAILABLE PHYSICAL PROCESSORS.

• IT WORKS WELL FOR TASKS RUNNING MORE OR
LESS INDEPENDENTLY ie., FOR TASKS HAVING
LOW COMMUNICATION AND SYNCHRONIZATION
REQUIREMENTS.
• COMM AND SYNC IS IMPLEMENTED EITHER
THROUGH THE SHARED MEMORY OR BY
MESSAGE SYSTEM OR THROUGH THE HYBRID
APPROACH.

• SHARED MEMORY ARCHITECTURE:
MEMORY
CPU CPU CPU
COMMON BUS ARCHITECTURE
MEM0 MEM1 MEMn
PROCESSOR MEMORY SWITCH
CPU CPU CPU
SWITCH BASED
MULTIPROCESSOR

• MESSAGE BASED ARCHITECTURE:
………………
PE 1 PE 2 PE n
CONNECTION NETWORK

• HYBRID ARCHITECTURE:
PE 1 PE 2 PE n
CONNECTION NETWORK
MEM 1 MEM 2 MEM k

• ON A SINGLE BUS SYSTEM, THERE IS A LIMIT ON THE
NUMBER OF PROCESSORS THAT CAN BE OPERATED IN
PARALLEL.
• IT IS USUALLY OF THE ORDER OF 10.
• COMM NETWORK HAS THE ADVANTAGE THAT THE NO
OF PROCESSORS CAN GROW WITHOUT LIMIT, BUT THE
CONNECTION AND COMM COST MAY DOMINATE AND
THUS SATURATE THE PERFORMANCE GAIN.
• DUE TO THIS REASON, HYBRID APPROACH MAY BE
FOLLOWED
• MANY SYSTEMS USE A COMMON BUS ARCH FOR
GLOBAL MEM, DISK AND I/O WHILE THE PROC MEM
TRAFFIC IS HANDLED BY SEPARATE BUS.

DATA FLOW COMPUTERS
• A NEW FINE GRAIN PARALLEL PROCESSING
APPROACH BASED ON DATAFLOW COMPUTING
MODEL HAS BEEN SUGGESTED BY JACK DENNIS
IN 1975.
• HERE, A NO OF DATA FLOW OPERATORS, EACH
CAPABLE OF DOING AN OPERATION ARE
EMPLOYED.
• A PROGRAM FOR SUCH A MACHINE IS A
CONNECTION GRAPH OF THE OPERATORS.

DATA FLOW COMPUTERS
• THE OPERATORS FORM THE NODES OF THE
GRAPH WHILE THE ARCS REPRESENT THE DATA
MOVEMENT BETWEEN NODES.
• AN ARC IS LABELED WITH A TOKEN TO INDICATE
THAT IT CONTAINS THE DATA.
• A TOKEN IS GENERATED ON THE OUTPUT OF A
NODE WHEN IT COMPUTES THE FUNCTION
BASED ON THE DATA ON ITS INPUT ARCS.

DATA FLOW COMPUTERS
• THIS IS KNOWN AS FIRING OF THE NODE.
• A NODE CAN FIRE ONLY WHEN ALL OF ITS INPUT
ARCS HAVE TOKENS AND THERE IS NO TOKEN
ON THE OUTPUT ARC.
• WHEN A NODE FIRES, IT REMOVES THE INPUT
TOKENS TO SHOW THAT THE DATA HAS BEEN
CONSUMED.
• USUALLY, COMPUTATION STARTS WITH
ARRIVAL OF DATA ON THE INPUT NODES OF THE
GRAPH.

DATA FLOW COMPUTERS
• DATA FLOW GRAPH FOR THE COMPUTATION:
• A = 5 + C – D
5
C
D
+ -
COMPUTATION PROGRESSES
AS PER DATA AVAILABILITY

DATA FLOW COMPUTERS
• MANY CONVENTIONAL MACHINES EMPLOYING
MULTIPLE FUNCTIONAL UNITS EMPLOY THE DATA
FLOW MODEL FOR SCHEDULING THE FUNCTIONAL
UNITS.
• EXAMPLE EXPERIMENTAL MACHINES ARE
MANCHESTER MACHINE (1984) AND MIT MACHINE.
• THE DATA FLOW COMPUTERS PROVIDE FINE
GRANULARITY OF PARALLEL PROCESSING, SINCE THE
DATA FLOW OPERATORS ARE TYPICALLY
ELEMENTARY ARITHMETIC AND LOGIC OPERATORS.

DATA FLOW COMPUTERS
• IT MAY PROVIDE AN EFFECTIVE SOLUTION FOR USING
VERY LARGE NUMBER OF COMPUTING ELEMENTS IN
PARALLEL.
• WITH ITS ASYNCHRONOUS DATA DRIVEN CONTROL, IT
HAS A PROMISE FOR EXPLOITATION OF THE
PARALLELISM AVAILABLE BOTH IN THE PROBLEM AND
THE MACHINE.
• CURRENT IMPLEMENTATIONS ARE NO BETTER THAN
CONVENTIONAL PIPELINED MACHINES EMPLOYING
MULTIPLE FUNCTIONAL UNITS.

SYSTOLIC ARCHITECTURES
• THE ADVENT OF VLSI HAS MADE IT POSSIBLE TO
DEVELOP SPECIAL ARCHITECTURES SUITABLE
FOR DIRECT IMPLEMENTATION IN VLSI.
• SYSTOLIC ARCHITECTURES ARE BASICALLY
PIPELINES OPERATING IN ONE OR MORE
DIMENSIONS.
• THE NAME SYSTOLIC HAS BEEN DERIVED FROM
THE ANALOGY OF THE OPERATION OF BLOOD
CIRCULATION SYSTEM THROUGH THE HEART.

• CONVENTIONAL ARCHITECTURES OPERATE ON
THE DATA USING LOAD AND STORE OPERATIONS
FROM THE MEMORY.
• PROCESSING USUALLY INVOLVES SEVERAL
OPERATIONS.
• EACH OPERATION ACCESSES THE MEMORY FOR
DATA, PROCESSES IT AND THEN STORES THE
RESULT. THIS REQUIRES A NO OF MEM
REFERENCES.

• CONVENTIONAL PROCESSING:
MEMORY
F1 F2 Fn
MEMORY
F1 F2 Fn
• SYSTOLIC PROCESSING

• IN SYSTOLIC PROCESSING, DATA TO BE PROCESSED
FLOWS THROUGH VARIOUS OPERATION STAGES AND
THEN FINALLY IT IS PUT IN THE MEMORY.
• SUCH AN ARCHITECTURE CAN PROVIDE BERY HIGH
COMPUTING THROUGHPUT DUE TO REGULAR
DATAFLOW AND PIPELINE OPERATION.
• IT MAY BE USEFUL IN DESIGNING SPECIAL PROCESSORS
FOR GRAPHIC, SIGNAL & IMAGE PROCESSING.

PERFORMANCE OF
PARALLEL COMPUTERS
• AN IMPORTANT MEASURE OF PARALLEL
ARCHITECTURE IS SPEEDUP.
• LET n = NO. OF PROCESSORS; Ts = SINGLE PROC.
EXEC TIME; Tn = N PROC. EXEC. TIME,
• THEN
• SPEEDUP S = Ts/Tn

AMDAHL’S LAW
• 1967
• BASED ON A VERY SIMPLE OBSERVATION.
• A PROGRAM REQUIRING TOTAL TIME T FOR
SEQUENTIAL EXECUTION SHALL HAVE SOME
PART WHICH IS INHERENTLY SEQUENTIAL.
• IN TERMS OF TOTAL TIME TAKEN TO SOLVE THE
PROBLEM, THIS FRACTION OF COMPUTING TIME
IS AN IMPORTANT PARAMETER.

AMDAHL’S LAW
• LET f = SEQ. FRACTION FOR A GIVEN PROGRAM.
• AMDAHL’S LAW STATES THAT THE SPEED UP OF
A PARALLEL COMPUTER IS LIMITED BY
S <= 1/[f + (1 – f )/n]
 SO, IT SAYS THAT WHILE DESIGNING A
PARALLEL COMP, CONNECT SMALL NO OF
EXTREMELY POWERFUL PROCS AND LARGE NO
OF INEXPENSIVE PROCS.

AMDAHL’S LAW
• CONSIDER TWO PARALLEL COMPS. Me AND Mi.
Me IS BUILT USING POWERFUL PROCS. CAPABLE
OF EXECUTING AT A SPEED OF M MEGAFLOPS.
• THE COMP Mi IS BUILT USING CHEAP PROCS.
AND EACH PROC. OF Mi EXECUTES r.M
MEGAFLOPS, WHERE 0 < r < 1
• IF THE MACHINE Me ATTEMPTS A COMPUTATION
WHOSE INHERENTLY SEQ.FRACTION f > r THEN
Mi WILL EXECUTE COMPS. MORE SLOWLY THAN
A SINGLE PROC. OF Mi.

AMDAHL’S LAW
• PROOF:
LET W = TOTAL WORK; M = SPEED OF Mi (IN Mflops)
R.m = SPEED OF PE OF Ma; f.W = SEQ WORK OF JOB;
T(Ma) = TIME TAKEN BY Ma FOR THE WORK W,
T(Mi) = TIME TAKEN BY Mi FOR THE WORK W, THEN
TIME TAKEN BY ANY COMP =
T = AMOUNT OF WORK/SPEED

AMDAHL’S LAW
• T(Ma) = TIME FOR SEQ PART + TIME FOR
PARALLEL PART
= ((f.W)/(r.M)) + [((1-f).W/n)/(r.M)] = (W/M).(f/r) IF n IS
INFINITELY LARGE.
T(Me) = (W/M) [ASSUMING ONLY 1 PE]
SO IF f > r, THEN T(Ma) > T(Mi)

AMDAHL’S LAW
• THE THEOREM IMPLIES THAT A SEQ COMPONENT
FRACTION ACCEPTABLE FOR THE MACHINE Mi
MAY NOT BE ACCEPTABLE FOR THE MACHINE
Ma.
• IT IS NOT GOOD TO HAVE A LARGER PROCESSING
POWER THAT GOES AS A WASTE. PROCS MUST
MAINTAIN SOME LEVEL OF EFFICIENCY.

AMDAHL’S LAW
• RELATION BETWEEN EFFICIENCY e AND SEQ FRACTION
r:
• S <= 1/[f + (1 – f )/n]
• EFFICIENCY e = S/n
• SO, e <= 1/[f.n + 1 – f ]
• IT SAYS THAT FOR CONSTANT EFFICIENCY, THE
FRACTION OF SEQ COMP OF AN ALGO MUST BE
INVERSELY PROPORTIONAL TO THE NO OF
PROCESSORS.
• THE IDEA OF USING LARGE NO OF PROCS MAY THUS BE
GOOD FOR ONLY THOSE APPLICATIONS FOR WHICH IT
IS KNOWN THAT THE ALGOS HAVE A VERY SMALL SEQ
FRACTION f.

MINSKY’S CONJECTURE
• 1970
• FOR A PARALLEL COMPUTER WITH n PROCS, THE
SPEEDUP S SHALL BE PROPORTIONAL TO log2n.
• MINSKY’S CONJECTURE WAS VERY BAD FOR THE
PROPONENTS OF LARGE SCALE PARALLEL
ARCHITECTURES.
• FLYNN & HENNESSY (1980) THEN GAVE THAT
SPEEDUP OF n PROCESSOR PARALEL SYSTEM IS
LIMITED BY S<= [n/(log2n)]

PARALLEL ALGORITHMS
• IMP MEASURE OF THE PERFORMANCE OF ANY
ALGO IS ITS TIME AND SPACE COMPLEXITY.
THEY ARE SPECIFIED AS SOME FUNCTION OF THE
PROBLEM SIZE.
• MANY TIMES, THEY DEPEND UPON THE USED
DATA STRUCTURE.
• SO, ANOTHER IMP MEASURE IS THE
PREPROCESSING TIME COMPLEXITY TO
GENERATE THE DESIRED DATA STRUCTURE.

PARALLEL ALGORITHMS
• PARALLEL ALGOS ARE THE ALGOS TO BE RUN
ON PARALLEL MACHINE.
• SO, COMPLEXITY OF COMM AMONGST
PROCESORS ALSO BECOMES AN IMPORTANT
MEASURE.
• SO, AN ALGO MAY FARE BADLY ON ONE
MACHINE AND MUCH BETTER ON THE OTHER.

PARALLEL ALGORITHMS
• DUE TO THIS REASON, MAPPING OF THE ALGO ON
THE ARCHITECTURE IS AN IMP ACTIVITY IN THE
STUDY OF PARALLEL ALGOS.
• SPEEDUP AND EFFICIENCY ARE ALSO IMP
PERFORMANCE MEASURES FOR A PARALLEL
ALGO WHEN MAPPED ON TO A GIVEN
ARCHITECTURE.

PARALLEL ALGORITHMS
• A PARALLEL ALGO FOR A GIVEN PROBLEM
MAY BE DEVELOPED USING ONE OR MORE OF
THE FOLLOWING:
1. DETECT AND EXPLOIT THE INHERENT
PARALLELISM AVAILABLE IN THE EXISTING
SEQUENTIAL ALGORITHM
2. INDEPENDENTLY INVENT A NEW PARALLEL
ALGORITHM
3. ADAPT AN EXISTING PARALLEL ALGO THAT
SOLVES A SIMILAR PROBLEM.

DISTRIBUTED PROCESSING
• PARALLEL PROCESSING DIFFERS FROM DISTRIBUTED
PROCESSING IN THE SENSE THAT IT HAS (1) CLOSE
COUPLING BETWEEN THE PROCESSORS & (2)
COMMUNICATION FAILURES MATTER A LOT.
• PROBLEMS MAY ARISE IN DISTRIBUTED PROCESSING
BECAUSE OF (1) TIME UNCERTAINTY DUE TO DIFFERING
TIME IN LOCAL CLOCKS, (2) INCOMPLETE INFO ABOUT
OTHER NODES IN THE SYSTEM, (3) DUPLICATE INFO
WHICH MAY NOT BE ALWAYS CONSISTENT.

PIPELINING PROCESSING
• A PIPELINE CAN WORK WELL WHEN:
1. THE TIME TAKEN BY EACH STAGE IS NEARLY
THE SAME.
2. IT REQUIRES A STEADY STEAM OF JOBS,
OTHERWISE UTILIZATION WILL BE POOR.
3. IT HONOURS THE PRECEDENCE CONSTRAINTS
OF SUB-STEPS OF JOBS.
IT IS THE MOST IMP PROPERTY OF PIPELINE. IT
ALLOWS PARALLEL EXECUTION OF JOBS
WHICH HAVE NO PARALLELISM WITHIN
INDIVIDUAL JOBS THEMSELVES.

• IN FACT, A JOB WHICH CAN BE BROKEN INTO A NO OF
SEQUENTIAL STEPS IS THE BASIS OF PIPELINE
PROCESSING.
• THIS IS DONE BY INTRODUCING TEMPORAL
PARALLELISM WHICH MEANS EXECUTING DIFFERENT
STEPS OF DIFFERENT JOBS INSIDE THE PIPELINE.
• THE PERFORMANCE IN TERMS OF THROUGHPUT IS
GUARANTEED IF THERE ARE ENOUGH JOBS TO BE
STREAMED THROUGH THE PIPELINE, ALTHOUGH AN
INDIVIDUAL JOB FINISHES WITH A DELAY EQUALLING
THE TOTAL DELAY OF ALL THE STAGES.

• THE FOURTH IMP THING IS THAT THE STAGES IN
THE PIPELINE ARE SPECIALIZED TO DO
PARTICULAR SUBFUNCTIONS, UNLIKE IN
CONVENTIONAL PARALLEL PROCESSORS WERE
EQUIPMENT IS REPLICATED.
• IT AMOUNTS TO SAYING THAT DUE TO
SPECIALIZATION, THE STAGE PROC COULD BE
DESIGNED WITH BETTER COST AND SPEED,
OPTIMISED FOR THE SPECIALISED FUNCTION OF
THE STAGE

PERFORMANCE MEASURES
OF PIPELINE
• EFFICIENCY, SPEEDUP AND THROUGHPUT
• EFFICIENCY: LET n BE THE LENGTH OF PIPE AND
m BE THE NO OF TASKS RUN ON THE PIPE, THEN
EFFICIENCY e CAN BE DEFINED AS
• e = [(m.n)/((m+n-1).(n))]
• WHEN n>>m, e TENDS TO m/n (A SMALL FRACTION)
• WHEN n<<m, e TENDS TO 1
• WHEN n = m, e IS APPROX 0.5 (m,n > 4)

OF PIPELINE
• SPEEDUP = S = [((n.ts).m)/((m+n-1).ts)]
= [(m.n)/(n+m-1)]
 WHEN n>>m, S=m (NO. OF TASKS RUN)
 WHEN n<<m, S=n (NO OF STAGES)
 WHEN n = m, S=n/2 (m,n > 4)

OF PIPELINE
• THROUGHPUT = Th = [m/((n+m-1).ts)] = e/ts WHERE ts IS
TIME THAT ELAPSES AT 1 STAGE.
• WHEN n>>m, Th = m/(n.ts)
• WHEN n<<m, Th = 1/ts
• WHEN n = m, Th = 1/(2.ts) (n,m > 4)
• SO, SPEEDUP IS A FUNCTION OF n AND ts. FOR A GIVEN
TECHNOLOGY ts IS FIXED, SO AS LONG AS ONE IS FREE
TO CHOOSE n, THERE IS NO LIMIT ON THE SPEEDUP
OBTAINABLE FROM A PIPELINED MECHANISM.

OPTIMAL PIPE SEGMENTATION
• IN HOW MANY SUBFUNCTIONS A FUNCTION
SHOULD BE DIVIDED?
• LET n = NO OF STAGES, T= TIME FOR NON-
PIPELINED IMPLEMENTATION, D = LATCH DELAY
AND c = COST OF EACH STAGE
• STAGE COMPUTE TIME = T/n (SINCE T IS DIVIDED
EQUALLY FOR n STAGES)
• PIPELINE COST= c.n + k WHERE k IS A CONSTANT
REFLECTING SOME COST OVERHEAD.

OPTIMAL PIPE SEGMENTATION
• SPEED (TIME PER OUTPUT) = (T/n + D)
• ONE OF THE IMPORTANT PERFORMANCE
MEASURE IS THE PRODUCT OF SPEED AND COST
DENOTED BY p.
• p = [(T/n) + D).(c.n +k)] = T.c +D.c.n + (k.T)/n + k.D
• TO OBTAIN A VALUE OF n WHICH GIVES BEST
PERFORMANCE, WE DIFFERENTIATE p w r t n AND
EQUATE IT TO ZERO
• dp/dn = D.c –(k.T)/n2
= 0
• n = SQRT [(k.T)/(D.c)]

PIPELINE CONTROL
• IN A NON-PIPELINED SYSTEM, ONE INST IS FULLY EXECUTED
BEFORE THE NEXT ONE STARTS, THUS MATCHING THE ORDER
OF EXECUTION.
• IN A PIPELINED SYSTEM, INST EXECUTION IS OVERLAPPED.
SO, IT CAN CAUSE PROBLEMS IF NOT CONSIDERED PROPERLY
IN THE DESIGN OF CONTROL.
• EXISTENCE OF SUCH DEPENDENCIES CAUSES “HAZARDS”
• CONTROL STRUCTURE PLAYS AN IMP ROLE IN THE
OPERATIONAL EFFICIENCY AND THROUGHPUT OF THE
MACHINE.

PIPELINE CONTROL
• THERE ARE 2 TYPES OF CONTROL STRUCTURES
IMPLEMENTED ON COMMERCIAL SYSTEMS.
• THE FIRST ONE IS CHARACTERISED BY A STREAMLINE FLOW
OF THE INSTS IN THE PIPE.
• IN THIS, INSTS FOLLOW ONE AFTER ANOTHER SUCH THAT
THE COMPLETION ORDERING IS THE SAME AS THE ORDER OF
INITIATION.
• THE SYSTEM IS CONCEIVED AS A SEQUENCE OF FUNCTIONAL
MODULES THROUGH WHICH THE INSTS FLOW ONE AFTER
ANOTHER WITH AN “INTERLOCK” BETWEEN THE ADJACENT
STAGES TO ALLOW THE TRANSFER OF DATA FROM ONE
STAGE TO ANOTHER.

PIPELINE CONTROL
• THE INTERLOCK IS NECESSARY BECAUSE THE PIPE IS
ASYNCHRONOUS DUE TO VARIATIONS IN THE SPEEDS
OF DIFFERENT STAGES.
• IN THESE SYSTEMS, THE BOTTLRNECKS APPEAR
DYNAMICALLY AT ANY STAGE AND THE INPUT TO IT IS
HALTED TEMPORARILY.
• THE SECOND TYPE OF CONTROL IS MORE FLEXIBLE,
POWERFUL BUT EXPENSIVE.

PIPELINE CONTROL
• IN SUCH SYSTEMS, WHEN A STAGE HAS TO SUSPEND THE
FLOW OF A PARTICULAR INSTRUCTION, IT ALLOWS OTHER
INSTS TO PASS THROUGH THE STAGE RESULTING IN AN OUT-
OF-TURN EXECUTION OF THE INSTS.
• THE CONTROL MECHANISM IS DESIGNED SUCH THAT EVEN
THOUGH THE INSTS ARE EXECUTED OUT-OF-TURN, THE
BEHAVIOUR OF THE PROGRAM IS SAME AS IF THEY WERE
EXECUTED IN THE ORIGINAL SEQUENCE.
• SUCH CONTROL IS DESIRABLE IN A SYSTEM HAVING
MULTIPLE ARITHMETIC PIPELINES OPERATING IN PARALLEL.

PIPELINE HAZARDS
• THE HARDWARE TECHNIQUE THAT DETECTS AND
RESOLVES HAZARDS IS CALLED INTERLOCK.
• A HAZARD OCCURS WHENEVER AN OBJECT WITHIN
THE SYSTEM (REF, FLAG, MEM LOCATION) IS ACCESSED
OR MODIFIED BY 2 SEPARATE INSTS THAT ARE CLOSE
ENOUGH IN THE PROGRAM SUCH THAT THEY MAY BE
ACTIVE SIMULTANEOUSLY IN THE PIPELINE.
• HAZARDS ARE OF 3 KINDS: RAW, WAR AND WAW

PIPELINE HAZARDS
• ASSUME THAT AN INST j LOGICALLY FOLLOWS AN INST i.
• RAW HAZARD: IT OCCURS BETWEEN 2 INSTS WHEN INST j
ATTEMPTS TO READ SOME OBJECT THAT IS BEING MODIFIED
BY INST i.
• WAR HAZARD: IT OCCURS BETWEEN 2 INSTS WHEN THE INST j
ATTEMPTS TO WRITE ONTO SOME OBJECT THAT IS BEING
READ BY THE INST i.
• WAW HAZARD: IT OCCURS WHEN THE INST j ATTEMPTS TO
WRITE ONTO SOME OBJECT THAT IS ALSO REQUIRED TO BE
MODIFIED BY THE INST i.

PIPELINE HAZARDS
• THE DOMAIN (READ SET) OF AN INST k, DENOTED BY Dk,
IS THE SET OF ALL OBJECTS WHOSE CONTENTS ARE
ACCESSED BY THE INST k.
• THE RANGE (WRITE SET) OF AN INST k, DENOTED BY Rk,
IS THE SET OF ALL OBJECTS UPDATED BY THE INST k.
• A HAZARD BETWEEN 2 INSTS i AND j (WHERE j FOLLOWS
i) OCCURS WHENEVER ANY OF THE FOLLOWING HOLDS:
• Ri * Dj <>{ } (RAW)
• Di * Rj <> { } (WAR)
• Ri * Rj <> { } (WAW), WHERE * IS INTERSECTION
OPERATION AND { } IS EMPTY SET.

HAZARD DETECTION & REMOVAL
• TECHNIQUES USED FOR HAZARD DETECTION CAN BE
CLASSIFIED INTO 2 CLASSES:
 CENTRALIZE ALL THE HAZARD DETECTION IN ONE
STAGE (USUALLY IU) AND COMPARE THE DOMAIN AND
RANGE SETS WITH THOSE OF ALL THE INSTS INSIDE
THE PIPELINE
 ALLOW THE INSTS TO TRAVEL THROUGH THE PIPELINE
UNTIL THE OBJECT EITHER FROM THE DOMAIN OR
RANGE IS REQUIRED BY THE INST. AT THIS POINT,
CHECK IS MADE FOR A POTENTIAL HAZARD WITH ANY
OTHER INST INSIDE THE PIPELINE.

• FIRST APPROACH IS SIMPLE BUT SUSPENDS THE
INST FLOW IN THE IU ITSELF, IF THE INST
FETCHED IS IN HAZARD WITH THOSE INSIDE THE
PIPELINE.
• THE SECOND APPROACH IS MORE FLEXIBLE BUT
THE HARDWARE REQUIRED GROWS AS A
SQUARE OF THE NO OF STAGES.

• THERE ARE 2 APPROACHS FOR HAZARD REMOVAL:
 SUSPEND THE PIPELINE INITIATION AT THE POINT OF
HAZARD. THUS, IF AN INST j DISCOVERS THAT THERE IS
A HAZARD WITH THE PREVIOUSLY INITIATED INST i,
THEN ALL THE INSTS j+1, j+2,… ARE STOPPED IN THEIR
TRACKS TILL THE INST i HAS PASSED THE POINT OF
HAZARD.
 SUSPEND j BUT ALLOW THE INSTS j+1, j+2, … TO FLOW.

• THE FIRST APPROACH IS SIMPLE BUT PENALIZES ALL THE
INSTS FOLLOWING j.
• SECOND APPROACH IS EXPENSIVE.
• IF THE PIPELINE STAGES HAVE ADDITIONAL BUFFERS BESIDES
A STAGING LATCH, THEN IT IS POSSIBLE TO SUSPEND AN INST
BECAUSE OF HAZARD.
• AT EACH POINT IN THE PIPELINE, WHERE DATA IS TO BE
ACCESSED AS AN INPUT TO SOME STAGE AND THERE IS A RAW
HAZARD, ONE CAN LOAD ONE OF THE STAGING LATCH NOT
WITH THE DATA BUT ID OF THE STAGE THAT WILL PRODUCE
IT.

• THE WAITING INST THEN IS FROZEN AT THIS STAGE UNTIL
THE DATA IS AVAILABLE.
• SINCE THE STAGE HAS MULTIPLE STAGING LATCHES IT CAN
ALLOW OTHER INSTS TO PASS THROUGH IT WHILE THE RAW
DEPENDENT ONE IS FROZEN.
• ONE CAN INCLUDE LOGIC IN THE STAGE TO FORWARD THE
DATA WHICH WAS IN RAW HAZARD TO THE WAITING STAGE.
• THIS FORM OF CONTROL ALLOWS HAZARD RESOLUTION
WITH THE MINIMUM PENALTY TO OTHER INSTS.

• THIS TECHNIQUE IS KNOWN BY THE NAME “INTERNAL
FORWARDING” SINCE THE STAGES ARE DESIGNED TO
CARRY OUT AUTOMATIC ROUTING OF THE DATA TO
THE REQUIRED PLACE USING IDENTIFICATION CODES
(IDs).
• IN FACT, MANY OF THE DATA DEPENDENT
COMPUTATIONS ARE CHAINED BY MEANS OF ID TAGS
SO THAT UNNECESSARY ROUTING IS ALSO AVOIDED.

MULTIPROCESSOR SYSTEMS
• IT IS A COMPUTER SYSTEM COMPRISING OF TWO OR MORE
PROCESSORS.
• AN INTERCONNECTION NETWORK LINKS THESE
PROCESSORS.
• THE MAIN OBJECTIVE IS TO ENHANCE THE PERFORMANCE
BY MEANS OF PARALLEL PROCESSING.
• IT FALLS UNDER THE MIMD ARCHITECTURE.
• BESIDES HIGH PERFORMANCE, IT PROVIDES THE
FOLLOWING BENEFITS: FAULT TOLERANCE & GRACEFUL
DEGRADATION; SCALABILITY & MODULAR GROWTH

CLASSIFICATION OF MULTI-PROCESSORS
• MULTI-PROCESSOR ARCHITECTURE:
TIGHTLY COUPLED LOOSELY COUPLED
UMA NUMA NORMA
NO REMOTE MEMORY ACCESS
IN A TIGHTLY COUPLED MULTI-PROCESSOR, MULTIPLE PROCS SHARE
INFO VIA COMMON MEM. HENCE, ALSO KNOWN AS SHARED MEM MULTI-
PROCESSOR SYSTEM. BESIDES GLOBAL MEM, EACH PROC CAN ALSO
HAVE LOCAL MEM DEDICATED TO IT.
DISTRIBUTED MEM MULTI-
PROCESSOR SYSTEM

SYMMETRIC
MULTIPROCESSOR
• IN UMA SYSTEM, THE ACCESS TIME FOR MEM IS EQUAL
FOR ALL THE PROCESSORS.
• A SMP SYSTEM IS AN UMA SYSTEM WITH IDENTICAL
PROCESSORS, EQUALLY CAPABLE IN PERFORMING
SIMILAR FUNCTIONS IN AN IDENTICAL MANNER.
• ALL THE PROCS. HAVE EQUAL ACCESS TIME FOR THE MEM
AND I/O RESOURCES.
• FOR THE OS, ALL SYSTEMS ARE SIMILAR AND ANY PROC.
CAN EXECUTE IT.
• THE TERMS UMA AND SMP ARE INTERCHANGABLY USED.

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