Fpga-based Implementation of Signal Processing Systems

An important working resource for engineers and researchers involved in the design, development, and implementation of signal processing systems

The last decade has seen a rapid expansion of the use of field programmable gate arrays (FPGAs) for a wide range of applications beyond traditional digital signal processing (DSP) systems. Written by a team of experts working at the leading edge of FPGA research and development, this second edition of FPGA-based Implementation of Signal Processing Systems has been extensively updated and revised to reflect the latest iterations of FPGA theory, applications, and technology. Written from a system-level perspective, it features expert discussions of contemporary methods and tools used in the design, optimization and implementation of DSP systems using programmable FPGA hardware. And it provides a wealth of practical insights—along with illustrative case studies and timely real-world examples—of critical concern to engineers working in the design and development of DSP systems for radio, telecommunications, audio-visual, and security applications, as well as bioinformatics, Big Data applications, and more. Inside you will find up-to-date coverage of:

• FPGA solutions for Big Data Applications, especially as they apply to huge data sets
• The use of ARM processors in FPGAs and the transfer of FPGAs towards heterogeneous computing platforms
• The evolution of High Level Synthesis tools—including new sections on Xilinx's HLS Vivado tool flow and Altera's OpenCL approach
• Developments in Graphical Processing Units (GPUs), which are rapidly replacing more traditional DSP systems

FPGA-based Implementation of Signal Processing Systems, 2nd Edition is an indispensable guide for engineers and researchers involved in the design and development of both traditional and cutting-edge data and signal processing systems. Senior-level electrical and computer engineering graduates studying signal processing or digital signal processing also will find this volume of great interest.

Roger Woods is a full professor and Research Director for the Electronics and Computer Engineering Cluster at Queen's University Belfast, Northern Ireland, UK.
John McAllister is an academic at Queen's University Belfast, Northern Ireland, UK.
Gaye Lightbody is a Lecturer within the School of Computing and Mathematics at Ulster University, Northern Ireland, UK.
Ying Yi is currently a Senior Software Engineer at SN Systems, a wholly owned subsidiary of Sony Interactive Entertainment Inc, England, UK.

Preface xv

List of Abbreviations xxi

1 Introduction to Field Programmable Gate Arrays 1

1.1 Introduction 1

1.2 Field Programmable Gate Arrays 2

1.3 Influence of Programmability 6

1.4 Challenges of FPGAs 8

Bibliography 9

2 DSP Basics 11

2.1 Introduction 11

2.2 Definition of DSP Systems 12

2.3 DSP Transformations 16

2.4 Filters 20

2.5 Adaptive Filtering 29

2.6 Final Comments 38

Bibliography 38

3 Arithmetic Basics 41

3.1 Introduction 41

3.2 Number Representations 42

3.3 Arithmetic Operations 47

3.4 Alternative Number Representations 55

3.5 Division 59

3.6 Square Root 60

3.7 Fixed-Point versus Floating-Point 64

3.8 Conclusions 66

Bibliography 67

4 Technology Review 70

4.1 Introduction 70

4.2 Implications of Technology Scaling 71

4.3 Architecture and Programmability 72

4.4 DSP Functionality Characteristics 74

4.5 Microprocessors 76

4.6 DSP Processors 82

4.7 Graphical Processing Units 86

4.8 System-on-Chip Solutions 88

4.9 Heterogeneous Computing Platforms 91

4.10 Conclusions 92

Bibliography 92

5 Current FPGA Technologies 94

5.1 Introduction 94

5.2 Toward FPGAs 95

5.3 Altera Stratix® V and 10 FPGA Family 98

5.4 Xilinx UltrascaleTM/Virtex-7 FPGA Families 103

5.5 Xilinx Zynq FPGA Family 107

5.6 Lattice iCE40isp FPGA Family 108

5.7 MicroSemi RTG4 FPGA Family 111

5.8 Design Stratregies for FPGA-based DSP Systems 112

5.9 Conclusions 114

Bibliography 114

6 Detailed FPGA Implementation Techniques 116

6.1 Introduction 116

6.2 FPGA Functionality 117

6.3 Mapping to LUT-Based FPGA Technology 123

6.4 Fixed-Coefficient DSP 125

6.5 Distributed Arithmetic 130

6.6 Reduced-Coefficient Multiplier 133

6.7 Conclusions 137

Bibliography 138

7 Synthesis Tools for FPGAs 140

7.1 Introduction 140

7.2 High-Level Synthesis 141

7.3 Xilinx Vivado 143

7.4 Control Logic Extraction Phase Example 144

7.5 Altera SDK for OpenCL 145

7.6 Other HLS Tools 147

7.7 Conclusions 150

Bibliography 150

8 Architecture Derivation for FPGA-based DSP Systems 152

8.1 Introduction 152

8.2 DSP Algorithm Characteristics 153

8.3 DSP Algorithm Representations 157

8.4 Pipelining DSP Systems 160

8.5 Parallel Operation 170

8.6 Conclusions 178

Bibliography 179

9 Complex DSP Core Design for FPGA 180

9.1 Introduction 180

9.2 Motivation for Design for Reuse 181

9.3 Intellectual Property Cores 182

9.4 Evolution of IP Cores 184

9.5 Parameterizable (Soft) IP Cores 187

9.6 IP Core Integration 195

9.7 Current FPGA-based IP Cores 197

9.8 Watermarking IP 198

9.9 Summary 198

Bibliography 199

10 AdvancedModel-Based FPGA Accelerator Design 200

10.1 Introduction 200

10.2 Dataflow Modeling of DSP Systems 201

10.3 Architectural Synthesis of Custom Circuit Accelerators from DFGs 204

10.4 Model-Based Development of Multi-Channel Dataflow Accelerators 205

10.5 Model-Based Development for Memory-Intensive Accelerators 219

10.6 Summary 223

References 223

11 Adaptive Beamformer Example 225

11.1 Introduction to Adaptive Beamforming 226

11.2 Generic Design Process 226

11.3 Algorithm to Architecture 231

11.4 Efficient Architecture Design 235

11.5 Generic QR Architecture 240

11.6 Retiming the Generic Architecture 246

11.7 Parameterizable QR Architecture 253

11.8 Generic Control 266

11.9 Beamformer Design Example 269

11.10 Summary 271

References 271

12 FPGA Solutions for Big Data Applications 273

12.1 Introduction 273

12.2 Big Data 274

12.3 Big Data Analytics 275

12.4 Acceleration 280

12.5 k-Means Clustering FPGA Implementation 283

12.6 FPGA-Based Soft Processors 286

12.7 System Hardware 290

12.8 Conclusions 293

Bibliography 293

13 Low-Power FPGA Implementation 296

13.1 Introduction 296

13.2 Sources of Power Consumption 297

13.3 FPGA Power Consumption 300

13.4 Power Consumption Reduction Techniques 302

13.5 Dynamic Voltage Scaling in FPGAs 303

13.6 Reduction in Switched Capacitance 305

13.7 Final Comments 316

Bibliography 317

14 Conclusions 319

14.1 Introduction 319

14.2 Evolution in FPGA Design Approaches 320

14.3 Big Data and the Shift toward Computing 320

14.4 Programming Flow for FPGAs 321

14.5 Support for Floating-Point Arithmetic 322

14.6 Memory Architectures 322

Bibliography 323

Index 325

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