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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
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