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FPGA-based Implementation of Signal Processing Systems Vital Source e-bog
Roger Woods, John McAllister, Gaye Lightbody og Ying Yi
(2017)
John Wiley & Sons
1.079,00 kr.
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FPGA-Based Implementation of Signal Processing Systems
Roger Woods, John McAllister, Gaye Lightbody og Ying Yi
(2017)
Sprog: Engelsk
John Wiley & Sons, Incorporated
1.175,00 kr.
Print on demand. Leveringstid vil være ca 2-3 uger.
Detaljer om varen
- 2. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: John Wiley & Sons (Februar 2017)
- Forfattere: Roger Woods, John McAllister, Gaye Lightbody og Ying Yi
- ISBN: 9781119077961
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.
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Print: 10 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 10 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- 2. Udgave
- Hardback: 360 sider
- Udgiver: John Wiley & Sons, Incorporated (Maj 2017)
- Forfattere: Roger Woods, John McAllister, Gaye Lightbody og Ying Yi
- ISBN: 9781119077954
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.
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
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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