MODERN PARALLEL PROGRAMMING WITH C++ AND ASSEMBLY LANGUAGE : x86 simd development using avx, avx2,... and avx-512

Learn the fundamentals of x86 Single instruction multiple data (SIMD) programming using C++ intrinsic functions and x86-64 assembly language. This book emphasizes x86 SIMD programming topics and technologies that are relevant to modern software development in applications which can exploit data level parallelism, important for the processing of big data, large batches of data and related important in data science and much more. __Modern Parallel Programming with C++ and Assembly Language__ is an instructional text that explains x86 SIMD programming using both C++ and assembly language. The book’s content and organization are designed to help you quickly understand and exploit the SIMD capabilities of x86 processors. It also contains an abundance of source code that is structured to accelerate learning and comprehension of essential SIMD programming concepts and algorithms. After reading this book, you will be able to code performance-optimized AVX, AVX2, and AVX-512 algorithms using either C++ intrinsic functions or x86-64 assembly language. **What You Will Learn** * Understand the essential details about x86 SIMD architectures and instruction sets including AVX, AVX2, and AVX-512. * Master x86 SIMD data types, arithmetic instructions, and data management operations using both integer and floating-point operands. * Code performance-enhancing functions and algorithms that fully exploit the SIMD capabilities of a modern x86 processor. * Employ C++ intrinsic functions and x86-64 assembly language code to carry out arithmetic calculations using common programming constructs including arrays, matrices, and user-defined data structures. * Harness the x86 SIMD instruction sets to significantly accelerate the performance of computationally intense algorithms in applications such as machine learning, image processing, computer graphics, statistics, and matrix arithmetic. * Apply leading-edge coding strategies and techniques to optimally exploit the x86 SIMD instruction sets for maximum possible performance. **Who This Book Is For** Intermediate to advanced programmers/developers in general. Readers of this book should have previous programming experience with modern C++ (i.e., ANSI C++11 or later) and Assembly. Some familiarity with Microsoft’s Visual Studio or the GNU toolchain will be helpful. The target audience for Modern X86 SIMD Programming are experienced software developers, programmers and maybe some hobbyists. Table of Contents About the Author About the Technical Reviewer Acknowledgments Introduction Chapter 1: SIMD Fundamentals What Is SIMD? Historical Overview of x86 SIMD SIMD Data Types SIMD Arithmetic SIMD Integer Arithmetic Wraparound vs. Saturated Arithmetic SIMD Floating-Point Arithmetic SIMD Data Manipulation Operations SIMD Programming Summary Chapter 2: AVX C++ Programming: Part 1 Integer Arithmetic Integer Addition Integer Subtraction Integer Multiplication Integer Bitwise Logical and Shift Operations Bitwise Logical Operations Shift Operations C++ SIMD Intrinsic Function Naming Conventions Image Processing Algorithms Pixel Minimum and Maximum Pixel Mean Intensity Summary Chapter 3: AVX C++ Programming: Part 2 Floating-Point Operations Floating-Point Arithmetic Floating-Point Compares Floating-Point Conversions Floating-Point Arrays Mean and Standard Deviation Distance Calculations Floating-Point Matrices Column Means Summary Chapter 4: AVX2 C++ Programming: Part 1 Integer Arithmetic Addition and Subtraction Unpacking and Packing Size Promotions Image Processing Pixel Clipping RGB to Grayscale Thresholding Pixel Conversions Summary Chapter 5: AVX2 C++ Programming: Part 2 Floating-Point Arrays Least Squares Floating-Point Matrices Matrix Multiplication Matrix (4 × 4) Multiplication Matrix (4 × 4) Vector Multiplication Matrix Inverse Summary Chapter 6: AVX2 C++ Programming: Part 3 Convolution Primer Convolution Math: 1D Convolution Math: 2D 1D Convolutions 2D Convolutions Nonseparable Kernel Separable Kernel Summary Chapter 7: AVX-512 C++ Programming: Part 1 AVX-512 Overview Integer Arithmetic Basic Arithmetic Merge Masking and Zero Masking Image Processing RGB to Grayscale Image Thresholding Image Statistics Summary Chapter 8: AVX-512 C++ Programming: Part 2 Floating-Point Arithmetic Basic Arithmetic Compare Operations Floating-Point Arrays Floating-Point Matrices Covariance Matrix Matrix Multiplication Matrix (4 x 4) Vector Multiplication Convolutions 1D Convolutions 2D Convolutions Summary Chapter 9: Supplemental C++ SIMD Programming Using CPUID Short Vector Math Library Rectangular to Polar Coordinates Body Surface Area Summary Chapter 10: X86-64 Processor Architecture Data Types Fundamental Data Types Numerical Data Types SIMD Data Types Strings Internal Architecture General-Purpose Registers Instruction Pointer RFLAGS Register Floating-Point and SIMD Registers MXCSR Register Instruction Operands Memory Addressing Condition Codes Summary Chapter 11: Core Assembly Language Programming: Part 1 Integer Arithmetic Addition and Subtraction Multiplication Division Calling Convention: Part 1 Memory Addressing Modes For-Loops Condition Codes Strings Summary Chapter 12: Core Assembly Language Programming: Part 2 Scalar Floating-Point Arithmetic Single-Precision Arithmetic Double-Precision Arithmetic Compares Conversions Scalar Floating-Point Arrays Calling Convention: Part 2 Stack Frames Using Nonvolatile General-Purpose Registers Using Nonvolatile SIMD Registers Macros for Function Prologues and Epilogues Summary Chapter 13: AVX Assembly Language Programming: Part 1 Integer Arithmetic Addition and Subtraction Multiplication Bitwise Logical Operations Arithmetic and Logical Shifts Image Processing Algorithms Pixel Minimum and Maximum Pixel Mean Intensity Summary Chapter 14: AVX Assembly Language Programming: Part 2 Floating-Point Operations Floating-Point Arithmetic Floating-Point Compares Floating-Point Arrays Mean and Standard Deviation Distance Calculations Floating-Point Matrices Summary Chapter 15: AVX2 Assembly Language Programming: Part 1 Integer Arithmetic Basic Operations Size Promotions Image Processing Pixel Clipping RGB to Grayscale Pixel Conversions Summary Chapter 16: AVX2 Assembly Language Programming: Part 2 Floating-Point Arrays Floating-Point Matrices Matrix Multiplication Matrix (4 × 4) Multiplication Matrix (4 × 4) Vector Multiplication Signal Processing Summary Chapter 17: AVX-512 Assembly Language Programming: Part 1 Integer Arithmetic Basic Operations Masked Operations Image Processing Image Thresholding Image Statistics Summary Chapter 18: AVX-512 Assembly Language Programming: Part 2 Floating-Point Arithmetic Basic Arithmetic Compare Operations Floating-Point Matrices Covariance Matrix Matrix Multiplication Matrix (4 x 4) Vector Multiplication Signal Processing Summary Chapter 19: SIMD Usage and Optimization Guidelines SIMD Usage Guidelines C++ SIMD Intrinsic Functions or x86 Assembly Language SIMD Software Development Guidelines Identify Functions for SIMD Techniques Select Default and Explicit SIMD Instruction Sets Establish Benchmark Timing Objectives Code Explicit SIMD Functions Benchmark Code to Measure Performance Optimize Explicit SIMD Code Repeat Benchmarking and Optimization Steps Optimization Guidelines and Techniques General Techniques Assembly Language Optimization Techniques SIMD Code Complexity vs. Performance Summary Appendix A: Source Code and Development Tools Source Code Download and Setup Development Tools Visual Studio and Windows Running a Source Code Example Creating a Visual Studio C++ Project Create a C++ Project Add an Assembly Language File Set Project Properties Edit the Source Code Build and Run the Project GCC and Linux Additional Configuration Build and Run Make Utility Appendix B: References and Resources C++ SIMD Intrinsic Function Documentation X86 Programming References X86 Processor Information Software Development Tools Algorithm References C++ References Utilities, Tools, and Libraries Index Learn the fundamentals of x86 Single instruction multiple data (SIMD) programming using C intrinsic functions and x86-64 assembly language. This book emphasizes x86 SIMD programming topics and technologies that are relevant to modern software development in applications which can exploit data level parallelism, important for the processing of big data, large batches of data and related important in data science and much more. Modern Parallel Programming with C and Assembly Language is an instructional text that explains x86 SIMD programming using both C and assembly language. The book’s content and organization are designed to help you quickly understand and exploit the SIMD capabilities of x86 processors. It also contains an abundance of source code that is structured to accelerate learning and comprehension of essential SIMD programming concepts and algorithms. After reading this book, you will be able to code performance-optimized AVX, AVX2, and AVX-512 algorithms using either C intrinsic functions or x86-64 assembly language. What You Will Learn Understand the essential details about x86 SIMD architectures and instruction sets including AVX, AVX2, and AVX-512. Master x86 SIMD data types, arithmetic instructions, and data management operations using both integer and floating-point operands. Code performance-enhancing functions and algorithms that fully exploit the SIMD capabilities of a modern x86 processor. Employ C intrinsic functions and x86-64 assembly language code to carry out arithmetic calculations using common programming constructs including arrays, matrices, and user-defined data structures. Harness the x86 SIMD instruction sets to significantly accelerate the performance of computationally intense algorithms in applications such as machine learning, image processing, computer graphics, statistics, and matrix arithmetic. Apply leading-edge coding strategies and techniques to optimally exploit the x86 SIMD instruction sets for maximum possible performance. Who This Book Is For Intermediate to advanced programmers/developers in general. Readers of this book should have previous programming experience with modern C (i.e., ANSI C 11 or later) and Assembly. Some familiarity with Microsoft’s Visual Studio or the GNU toolchain will be helpful. The target audience for Modern X86 SIMD Programming are experienced software developers, programmers and maybe some hobbyists.