CUDA for Engineers
An Introduction to High-Performance Parallel Computing
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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 ...
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 programsUnderstanding CUDA s parallelism model and C extensionsTransferring data between CPU and GPUManaging timing, profiling, error handling, and debuggingCreating 2D gridsInteroperating with OpenGL to provide real-time user interactivityPerforming basic simulations with differential equationsUsing stencils to manage related computations across threadsExploiting CUDA s shared memory capability to enhance performanceInteracting with 3D data: slicing, volume rendering, and ray castingUsing CUDA librariesFinding more CUDA resources and code
Realistic example applications include
Visualizing functions in 2D and 3DSolving differential equations while changing initial or boundary conditionsViewing/processing images or image stacksComputing inner products and centroidsSolving systems of linear algebraic equationsMonte-Carlo computations
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 programsUnderstanding CUDA s parallelism model and C extensionsTransferring data between CPU and GPUManaging timing, profiling, error handling, and debuggingCreating 2D gridsInteroperating with OpenGL to provide real-time user interactivityPerforming basic simulations with differential equationsUsing stencils to manage related computations across threadsExploiting CUDA s shared memory capability to enhance performanceInteracting with 3D data: slicing, volume rendering, and ray castingUsing CUDA librariesFinding more CUDA resources and code
Realistic example applications include
Visualizing functions in 2D and 3DSolving differential equations while changing initial or boundary conditionsViewing/processing images or image stacksComputing inner products and centroidsSolving systems of linear algebraic equationsMonte-Carlo computations
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