CUDA for Engineers: An Introduction to High-Performance Parallel Computing

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Practical example applications consist of

• Visualizing features in 2D and 3D
• Solving differential equations while changing preliminary or boundary circumstances
• Viewing/processing pictures or picture stacks
• Computing internal items and centroids
• Solving systems of linear algebraic equations
• Monte-Carlo computations

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Perfect for any scientist, engineer, or college student with at least introductory programming encounter, this instruction assumes no specialized history in GPU-structured or parallel computing. Within an appendix, the authors also present a refresher on C development for those who require it.

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See also

• Comparative Programming Languages (3rd Edition)
• Principles of Concurrent and Distributed Programming (2nd Edition)
• Peter Norton's Assembly Language Book for the IBM PC (The Peter Norton foundation series)