parallel and distributed systems

Institute for Software Science – University of Vienna

P.Brezany

Parallel and Distributed Systems

Peter Brezany

Institute for Software Science

University of Vienna


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Typical One-Processor Architecture (SISD

Architecture)

SISD : Single Instruction stream Single Data stream


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Array Processor (SIMD Architecture)

SIMD: Single Instructionstream Multiple Data streams


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Loop Parallelizing for SIMDSsA typical scientific program spends approx. 90% of its execution

timein loops.Example in Java:

float A[1000], B[1000]; for (int i = 1; i < 1000; i++) { A[i-1] = B[i]; }

The above loop can be expressed in Fortran 95 in the following way:

A(0:998) = B(1:999)

This statement can be directly mapped onto a SIMD processor.

There is an initiative to extend Java by similar constructs.


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Parallel Multi-Processor-Hardware

(MIMD Architectures)• Distributed-memory machines (DM Multiprocessors, DM MIMDS)– Each processor has local memory and disk– Communication via message-passing– Hard to program: explicit data distribution– Goal: minimize communication

• Shared-memory machines (SM Multiprocessors, SM MIMDs, SMPs)– Shared global address space and disk– Communication via shared memory variables– Ease of programming– Goal: maximize locality, minimize false sharing

• Current trend: Cluster of SMPs


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Distributed Memory Architecture

(Shared Nothing)

LocalMemory

LocalMemory

LocalMemory

LocalMemory

CPU CPU

Interconnection Network

CPUCPU


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DMM: Shared Disk Architecture

LocalMemory

LocalMemory

LocalMemory

LocalMemory

CPU CPU CPU CPU


Global Shared Disk Subsystem


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Loop Parallelizing for DM MIMDs

Example in Java:

float A[10], B[10];

for (int i = 1; i < 10; i++) { A[i] = B[i-1]; }

For two processors, P1 and P2, a straightforward solution would be:


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Loop Parallelizing for DM MIMDs (2)


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Loop Parallelizing for DM MIMDs (3)Code on P1: float A[5], B[5]; float temp; for (int i = 1; i < 6; i++) { if ( i == 5 ) { receive message from P2 into temp; A[i-1] = temp; { else A[i-1] = B[i]; } Code on P2: float A[5], B[5]; float temp; for (int i = 0; i < 5; i++) { if ( i == 0 ) { temp = B[0]; send temp to P1; { else A[i-1] = B[i]; }


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Shared Memory Architecture(Shared Everything, SMP)

CPU CPU


CPUCPU

Global Shared Memory


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Loop Parallelizing for SMPsExample in Java:

float A[1000], B[1000]; for (int i = 1; i < 1000; i++) { A[i-1] = B[i]; }

If we have, e.g. two processors, P1 and P2, a straightforward

(non-optimal) solution would be:

Code on P1: for (int i = 1; i < 500; i++) { A[i-1] = B[i]; } Code on P2: for (int i = 500; i < 1000; i++) { A[i-1] = B[i]; }Data elements of A and B are stored in the shared memory.


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Cluster of SMPs

CPU


CPU

CPU CPU

4-CPUSMP

CPU CPU

CPU CPU

4-CPUSMP

CPU CPU

CPU CPU

4-CPUSMP

CPU CPU

CPU CPU

4-CPUSMP


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Abstract Maschine Model


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Cluster von PCs


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Pipeline

No Pipeline


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Towards Parallel Databases


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Relational Data Model

Example

Cities Name Population LandMunich 1211617 BayernBremen 535058 Bremen. . . . . . . . .

Schema: (Cities: STRING, Population: INTEGER, Land: STRING

Relation (represented by a table): {(Munich, 1.211.617, Bayern), (Bremen, 535.058, Bremen), ...}

Key : {Name}


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Relational Data Model - Queries

SELECT <Attribute List>

FROM <Relation Name>

[WHERE <Condition>] – option

.......... other options

Example: This is equivalent to:

SELECT * SELECT Name, Population, LandFROM Cities FROM Cities

SELECT Name, LandFROM CitiesWHERE Population > 600000


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Grid Idea

parallel and distributed systems

Documents