Synthesis and optimization of DSP algorithms

177 Pages·2004·2.927 MB·English

by  Cheung, Peter Y. K., Luk, Wayne, Constantinides, George A

SYNTHESIS AND OPTIMIZATION
OF DSP ALGORITHMS
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Synthesis and Optimization
of DSP Algorithms
by
George A. Constantinides
Imperial College, London
Peter Y.K. Cheung
Imperial College, London
and
Wayne Luk
Imperial College, London
KLUWER ACADEMIC PUBLISHERS
NEW YORK,BOSTON, DORDRECHT, LONDON, MOSCOW
eBookISBN: 1-4020-7931-1
Print ISBN: 1-4020-7930-3
©2004 Kluwer Academic Publishers
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Print ©2004 Kluwer Academic Publishers
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To all progressive people
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Preface
Digital signal processing (DSP) has undergone an immense expansion since
the foundations of the subject were laid in the 1970s. New application areas
have arisen, and DSP technology is now essential to a bewildering array of
fieldssuchascomputervision,instrumentationandcontrol,datacompression,
speechrecognitionandsynthesis,digitalaudioandcameras,mobiletelephony,
echo cancellation, and even active suspension in the automotive industry.
In parallel to, and intimately linked with, the growth in application areas
hasbeenthegrowthinrawcomputationalpoweravailabletoimplementDSP
algorithms.Moore’slawcontinuesto holdinthe semiconductorindustry,res-
ulting every 18 months in a doubling of the number of computations we can
perform.
Despitetherapidlyincreasingperformanceofmicroprocessors,thecompu-
tational demands of many DSP algorithms continue to outstrip the available
computationalpower.Asaresult,manycustomhardwareimplementationsof
DSPalgorithmsareproduced-atimeconsumingandcomplexprocess,which
the techniques described in this book aim, at least partially, to automate.
Thisbookprovidesanoverviewofrecentresearchonhardwaresynthesisan
optimizationofcustomhardwareimplementationsofdigitalsignalprocessors.
Itfocusesontechniquesforautomatingtheproductionofarea-efficientdesigns
from a high-leveldescription,while satisfying user-specifiedconstraints.Such
techniques are shown to be applicable to both linear and nonlinear systems:
from finite impulse response (FIR) and infinite impulse response (IIR) filters
to designs for discrete cosine transform (DCT), polyphase filter banks, and
adaptive least mean square (LMS) filters.
This book is designed for those working near the interface of DSP al-
gorithm designand DSP implementation. It is our contentionthat this inter-
face is a very exciting place to be, and we hope this book may help to draw
the reader nearer to it.
London, George A. Constantinides
February 2004 Peter Y.K. Cheung
Wayne Luk
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Contents
1 Introduction............................................... 1
1.1 Objectives.............................................. 1
1.2 Overview............................................... 2
2 Background ............................................... 5
2.1 Digital Design for DSP Engineers.......................... 5
2.1.1 Microprocessorsvs. Digital Design................... 5
2.1.2 The Field-ProgrammableGate Array ................ 6
2.1.3 Arithmetic on FPGAs ............................. 7
2.2 DSP for Digital Designers ................................ 8
2.3 Computation Graphs .................................... 9
2.4 The Multiple Word-Length Paradigm ...................... 12
2.5 Summary............................................... 13
3 Peak Value Estimation .................................... 15
3.1 Analytic Peak Estimation ................................ 15
3.1.1 Linear Time-Invariant Systems...................... 16
3.1.2 Data-range Propagation............................ 22
3.2 Simulation-based Peak Estimation......................... 24
3.3 Hybrid Techniques....................................... 25
3.4 Summary............................................... 25
4 Word-Length Optimization ................................ 27
4.1 Error Estimation ........................................ 27
4.1.1 Word-Length Propagationand Conditioning .......... 29
4.1.2 Linear Time-Invariant Systems...................... 32
4.1.3 Extending to Nonlinear Systems..................... 38
4.2 Area Models ............................................ 42
4.3 Problem Definition and Analysis .......................... 45
4.3.1 Convexity and Monotonicity ........................ 45
4.4 Optimization Strategy 1: Heuristic Search .................. 51