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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 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 debugging

Creating 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