Read online ebook CUDA for Engineers : An Introduction to High-Performance Parallel Computing by Mete Yurtoglu in DOC, EPUB
9780134177410 English 013417741X " CUDA for Engineers " gives you direct, hands-on engagement with personal high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you ll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA s parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debuggingCreating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA s shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations ", Extremely low-cost graphics cards now possess computational capabilities that were once limited to supercomputers. Using CUDA, you can to liberate the power of NVIDIA graphics cards for a wide spectrum of non-graphics applications. CUDA for Engineers is the first guide specifically focused on using CUDA to write high-performance engineering and scientific applications. Ideal for any scientist, engineer, or student with at least introductory programming experience, this tutorial presents examples and reusable C code to jumpstart a wide variety of applications. You'll walk through moving from serial to parallel computation; computing values of a function in parallel; understanding 2D parallelism; simulating dynamics in the phase pla≠simulating heat conduction; interacting with 3D data; walking through a basic N-body simulation, and more. Written by a working engineer, this comfortable and conversational guide focuses on practical knowledge you need to solve real engineering and scientific problems with CUDA - at a small fraction of what it would have cost just a few years ago., Graphics cards now possess computational capabilities that were once limited tosupercomputers. If you have a computer that bills itself as a gaming system, you may already have serious computing power at your disposal just waiting to be unleashed. Using CUDA, you can liberate the power of NVIDIA graphics cards to address a wide spectrum of applications.CUDA for Engineersis the first guide specifically written to make the power of CUDA for creating high-performance engineering and scientific applications available to the broader technical community. Ideal for any scientist, engineer, or student with at least introductory programming experience, this tutorial presents examples and reusable C code to jumpstart a wide variety of applications. You'll walk through moving from serial to parallel computation, computing values of a function in parallel, understanding 2D parallelism, simulating dynamics in the phase plane and steady-state heat conduction, image processing, solving linear systems, interacting with 3D data, and more. All projects are fully developed with detailed building instructions given for all major platforms. Written by engineers who have experienced CUDA becoming an indispensable tool, this comfortable and conversational guide focuses on practical knowledge you need to solve real engineering and scientific problems with CUDA at a small fraction of what it would have cost just a few years ago."
9780134177410 English 013417741X " CUDA for Engineers " gives you direct, hands-on engagement with personal high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you ll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA s parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debuggingCreating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA s shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations ", Extremely low-cost graphics cards now possess computational capabilities that were once limited to supercomputers. Using CUDA, you can to liberate the power of NVIDIA graphics cards for a wide spectrum of non-graphics applications. CUDA for Engineers is the first guide specifically focused on using CUDA to write high-performance engineering and scientific applications. Ideal for any scientist, engineer, or student with at least introductory programming experience, this tutorial presents examples and reusable C code to jumpstart a wide variety of applications. You'll walk through moving from serial to parallel computation; computing values of a function in parallel; understanding 2D parallelism; simulating dynamics in the phase pla≠simulating heat conduction; interacting with 3D data; walking through a basic N-body simulation, and more. Written by a working engineer, this comfortable and conversational guide focuses on practical knowledge you need to solve real engineering and scientific problems with CUDA - at a small fraction of what it would have cost just a few years ago., Graphics cards now possess computational capabilities that were once limited tosupercomputers. If you have a computer that bills itself as a gaming system, you may already have serious computing power at your disposal just waiting to be unleashed. Using CUDA, you can liberate the power of NVIDIA graphics cards to address a wide spectrum of applications.CUDA for Engineersis the first guide specifically written to make the power of CUDA for creating high-performance engineering and scientific applications available to the broader technical community. Ideal for any scientist, engineer, or student with at least introductory programming experience, this tutorial presents examples and reusable C code to jumpstart a wide variety of applications. You'll walk through moving from serial to parallel computation, computing values of a function in parallel, understanding 2D parallelism, simulating dynamics in the phase plane and steady-state heat conduction, image processing, solving linear systems, interacting with 3D data, and more. All projects are fully developed with detailed building instructions given for all major platforms. Written by engineers who have experienced CUDA becoming an indispensable tool, this comfortable and conversational guide focuses on practical knowledge you need to solve real engineering and scientific problems with CUDA at a small fraction of what it would have cost just a few years ago."