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Vector and SIMD Processors

Vector

SIMD

processor

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Vector and SIMD Processors

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Vector and SIMD

Processors

Eric Welch & James Evans

Multiple Processor Systems

Spring 2013

Outline

• Introduction

• Traditional Vector Processors

o History & Description

o Advantages

o Architectures

o Components

o Performance Optimizations

• Modern SIMD Processors

o Introduction

o Architectures

o Use in signal and image processing

History of Vector Processors

• Early Work

o Development started in the early 1960s at Westinghouse

 Goal of the Solomon project was to substantially increase arithmetic

performance by using many simple co-processors under the control of

a single master CPU

 Allowed single algorithm to be applied to large data set

• Supercomputers

o Dominated supercomputer design through the 1970s into the 1990s

o Cray platforms were the most notable vector supercomputers

 Cray -1: Introduced in 1976

 Cray-2, Cray X-MP, Cray Y-MP

o Demise

 In the late 1990s, the price-to-

performance ratio drastically

increased for conventional

microprocessor designs

Description of Vector Processors

• CPU that implements an instruction set that operates on

1-D arrays, called vectors

• Vectors contain multiple data elements

• Number of data elements per vector is typically referred

to as the vector length

• Both instructions and data are pipelined to reduce

decoding time

add r3, r1, r2

SCALAR

(1 operation)

v1 v2

vector

length

add.vv v3, v1, v2

VECTOR

(N operations)

Advantages of Vector Processors

• Require Lower Instruction Bandwith

o Reduced by fewer fetches and decodes

• Easier Addressing of Main Memory

o Load/Store units access memory with known patterns

• Elimination of Memory Wastage

o Unlike cache access, every data element that is requested by the

processor is actually used – no cache misses

o Latency only occurs once per vector during pipelined loading

• Simplification of Control Hazards

o Loop-related control hazards from the loop are eliminated

• Scalable Platform

o Increase performance by using more hardware resources

• Reduced Code Size

o Short, single instruction can describe N operations

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