Produktbild: Algorithms and Parallel Computing

Algorithms and Parallel Computing

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

19.04.2011

Verlag

John Wiley & Sons

Seitenzahl

368

Maße (L/B/H)

24/16,1/2,4 cm

Gewicht

712 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-90210-3

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

19.04.2011

Verlag

John Wiley & Sons

Seitenzahl

368

Maße (L/B/H)

24/16,1/2,4 cm

Gewicht

712 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-90210-3

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Algorithms and Parallel Computing
  • Preface xiii

    List of Acronyms xix

    1 Introduction 1

    1.1 Introduction 1

    1.2 Toward Automating Parallel Programming 2

    1.3 Algorithms 4

    1.4 Parallel Computing Design Considerations 12

    1.5 Parallel Algorithms and Parallel Architectures 13

    1.6 Relating Parallel Algorithm and Parallel Architecture 14

    1.7 Implementation of Algorithms: A Two-Sided Problem 14

    1.8 Measuring Benefi ts of Parallel Computing 15

    1.9 Amdahl's Law for Multiprocessor Systems 19

    1.10 Gustafson-Barsis's Law 21

    1.11 Applications of Parallel Computing 22

    2 Enhancing Uniprocessor Performance 29

    2.1 Introduction 29

    2.2 Increasing Processor Clock Frequency 30

    2.3 Parallelizing ALU Structure 30

    2.4 Using Memory Hierarchy 33

    2.5 Pipelining 39

    2.6 Very Long Instruction Word (VLIW) Processors 44

    2.7 Instruction-Level Parallelism (ILP) and Superscalar Processors 45

    2.8 Multithreaded Processor 49

    3 Parallel Computers 53

    3.1 Introduction 53

    3.2 Parallel Computing 53

    3.3 Shared-Memory Multiprocessors (Uniform Memory Access [UMA]) 54

    3.4 Distributed-Memory Multiprocessor (Nonuniform Memory Access [NUMA]) 56

    3.5 SIMD Processors 57

    3.6 Systolic Processors 57

    3.7 Cluster Computing 60

    3.8 Grid (Cloud) Computing 60

    3.9 Multicore Systems 61

    3.10 SM 62

    3.11 Communication Between Parallel Processors 64

    3.12 Summary of Parallel Architectures 67

    4 Shared-Memory Multiprocessors 69

    4.1 Introduction 69

    4.2 Cache Coherence and Memory Consistency 70

    4.3 Synchronization and Mutual Exclusion 76

    5 Interconnection Networks 83

    5.1 Introduction 83

    5.2 Classification of Interconnection Networks by Logical Topologies 84

    5.3 Interconnection Network Switch Architecture 91

    6 Concurrency Platforms 105

    6.1 Introduction 105

    6.2 Concurrency Platforms 105

    6.3 Cilk++ 106

    6.4 OpenMP 112

    6.5 Compute Unifi ed Device Architecture (CUDA) 122

    7 Ad Hoc Techniques for Parallel Algorithms 131

    7.1 Introduction 131

    7.2 Defining Algorithm Variables 133

    7.3 Independent Loop Scheduling 133

    7.4 Dependent Loops 134

    7.5 Loop Spreading for Simple Dependent Loops 135

    7.6 Loop Unrolling 135

    7.7 Problem Partitioning 136

    7.8 Divide-and-Conquer (Recursive Partitioning) Strategies 137

    7.9 Pipelining 139

    8 Nonserial-Parallel Algorithms 143

    8.1 Introduction 143

    8.2 Comparing DAG and DCG Algorithms 143

    8.3 Parallelizing NSPA Algorithms Represented by a DAG 145

    8.4 Formal Technique for Analyzing NSPAs 147

    8.5 Detecting Cycles in the Algorithm 150

    8.6 Extracting Serial and Parallel Algorithm Performance Parameters 151

    8.7 Useful Theorems 153

    8.8 Performance of Serial and Parallel Algorithms on Parallel Computers 156

    9 z-Transform Analysis 159

    9.1 Introduction 159

    9.2 Definition of z-Transform 159

    9.3 The 1-D FIR Digital Filter Algorithm 160

    9.4 Software and Hardware Implementations of the z-Transform 161

    9.5 Design 1: Using Horner's Rule for Broadcast Input and Pipelined Output 162

    9.6 Design 2: Pipelined Input and Broadcast Output 163

    9.7 Design 3: Pipelined Input and Output 164

    10 Dependence Graph Analysis 167

    10.1 Introduction 167

    10.2 The 1-D FIR Digital Filter Algorithm 167

    10.3 The Dependence Graph of an Algorithm 168

    10.4 Deriving the Dependence Graph for an Algorithm 169

    10.5 The Scheduling Function for the 1-D FIR Filter 171

    10.6 Node Projection Operation 177

    10.7 Nonlinear Projection Operation 179

    10.8 Software and Hardware Implementations of the DAG Technique 180

    11 Computational Geometry Analysis 185

    11.1 Introduction 185

    11.2 Matrix Multiplication Algorithm 185

    11.3 The 3-D Dependence Graph and Computation Domain D 186

    11.4 The Facets and Vertices of D 188

    11.5 The Dependence Matrices of the Algorithm Variables 188

    11.6 Nullspace of Dependence Matrix: The Broadcast Subdomain B 189

    11.7 Design Space Exploration: Choice of Broadcasting versus Pipelining Variables 192

    11.8 Data Scheduling 195

    11.9 Projection Operation Using the Linear Projection Operator 200

    11.10 Effect of Projection Operation on Data 205

    11.11 The Resulting Multithreaded/Multiprocessor Architecture 206

    11.12 Summary of Work Done in this Chapter 207

    12 Case Study: One-Dimensional IIR Digital Filters 209

    12.1 Introduction 209

    12.2 The 1-D IIR Digital Filter Algorithm 209

    12.3 The IIR Filter Dependence Graph 209

    12.4 z-Domain Analysis of 1-D IIR Digital Filter Algorithm 216

    13 Case Study: Two- and Three-Dimensional Digital Filters 219

    13.1 Introduction 219

    13.2 Line and Frame Wraparound Problems 219

    13.3 2-D Recursive Filters 221

    13.4 3-D Digital Filters 223

    14 Case Study: Multirate Decimators and Interpolators 227

    14.1 Introduction 227

    14.2 Decimator Structures 227

    14.3 Decimator Dependence Graph 228

    14.4 Decimator Scheduling 230

    14.5 Decimator DAG for s1 = [1 0] 231

    14.6 Decimator DAG for s2 = [1 ¿1] 233

    14.7 Decimator DAG for s3 = [1 1] 235

    14.8 Polyphase Decimator Implementations 235

    14.9 Interpolator Structures 236

    14.10 Interpolator Dependence Graph 237

    14.11 Interpolator Scheduling 238

    14.12 Interpolator DAG for s1 = [1 0] 239

    14.13 Interpolator DAG for s2 = [1 ¿1] 241

    14.14 Interpolator DAG for s3 = [1 1] 243

    14.15 Polyphase Interpolator Implementations 243

    15 Case Study: Pattern Matching 245

    15.1 Introduction 245

    15.2 Expressing the Algorithm as a Regular Iterative Algorithm (RIA) 245

    15.3 Obtaining the Algorithm Dependence Graph 246

    15.4 Data Scheduling 247

    15.5 DAG Node Projection 248

    15.6 DESIGN 1: Design Space Exploration When s ?­?n[1 1]t 249

    15.7 DESIGN 2: Design Space Exploration When s ?­?n[1 ¿1]t 252

    15.8 DESIGN 3: Design Space Exploration When s = [1 0]t 253

    16 Case Study: Motion Estimation for Video Compression 255

    16.1 Introduction 255

    16.2 FBMAs 256

    16.3 Data Buffering Requirements 257

    16.4 Formulation of the FBMA 258

    16.5 Hierarchical Formulation of Motion Estimation 259

    16.6 Hardware Design of the Hierarchy Blocks 261

    17 Case Study: Multiplication over GF(2m) 267

    17.1 Introduction 267

    17.2 The Multiplication Algorithm in GF(2m) 268

    17.3 Expressing Field Multiplication as an RIA 270

    17.4 Field Multiplication Dependence Graph 270

    17.5 Data Scheduling 271

    17.6 DAG Node Projection 273

    17.7 Design 1: Using d1 = [1 0]t 275

    17.8 Design 2: Using d2 = [1 1]t 275

    17.9 Design 3: Using d3 = [1 ¿1]t 277

    17.10 Applications of Finite Field Multipliers 277

    18 Case Study: Polynomial Division over GF(2) 279

    18.1 Introduction 279

    18.2 The Polynomial Division Algorithm 279

    18.3 The LFSR Dependence Graph 281

    18.4 Data Scheduling 282

    18.5 DAG Node Projection 283

    18.6 Design 1: Design Space Exploration When s1 = [1 ¿1] 284

    18.7 Design 2: Design Space Exploration When s2 = [1 0] 286

    18.8 Design 3: Design Space Exploration When s3 = [1 ¿0.5] 289

    18.9 Comparing the Three Designs 291

    19 The Fast Fourier Transform 293

    19.1 Introduction 293

    19.2 Decimation-in-Time FFT 295

    19.3 Pipeline Radix-2 Decimation-in-Time FFT Processor 298

    19.4 Decimation-in-Frequency FFT 299

    19.5 Pipeline Radix-2 Decimation-in-Frequency FFT Processor 303

    20 Solving Systems of Linear Equations 305

    20.1 Introduction 305

    20.2 Special Matrix Structures 305

    20.3 Forward Substitution (Direct Technique) 309

    20.4 Back Substitution 312

    20.5 Matrix Triangularization Algorithm 312

    20.6 Successive over Relaxation (SOR) (Iterative Technique) 317

    20.7 Problems 321

    21 Solving Partial Differential Equations Using Finite Difference Method 323

    21.1 Introduction 323

    21.2 FDM for 1-D Systems 324

    References 331

    Index 337