A roadmap for developers facing the challenge of developing applications to effectively use GPUs with CUDA to achieve efficiency and performance goals
1. First Programs and How to Think in CUDA
2. CUDA for Machine Learning and Optimization
3. The CUDA Tool Suite: Profiling a PCA/NLPCA Functor
4. The CUDA Execution Model
5. CUDA Memory
6. Efficiently Using GPU Memory
7. Techniques to Increase Parallelism
8. CUDA for All GPU and CPU Applications
9. Mixing CUDA and Rendering
10. CUDA in a Cloud and Cluster Environments
11. CUDA for Real Problems: Monte Carlo, Modeling, and More
12. Application Focus on Live Streaming Video
Rob Farber has served as a scientist at the Irish Center for High-End Computing, U.S. national labs in Los Alamos, Berkeley, and the Pacific Northwest, and external faculty at the Santa Fe Institute. His articles have appeared in Dr. Dobb's Journal and Scientific Computing, among others.
"The book by Rob Faber on CUDA Application Design and Development
is required reading for anyone who wants to understand and
efficiently program CUDA for scientific and visual programming. It
provides a hands-on exposure to the details in a readable and easy
to understand form." --Jack Dongarra, Innovative Computing
Laboratory, EECS Department, University of Tennessee
"GPUs have the potential to take computational simulations to new
levels of scale and detail. Many scientists are already realising
these benefits, tackling larger and more complex problems that are
not feasible on conventional CPU-based systems. This book provides
the tools and techniques for anyone wishing to join these pioneers,
in an accessible though thorough text that a budding CUDA
programmer would do well to keep close to hand." --Dr. George
Beckett, EPCC, University of Edinburgh
"With his book, Farber takes us on a journey to the exciting world
of programming multi-core processor machines with CUDA. Farber's
pragmatic approach is effective in guiding the reader across
challenges and their solutions. Farber's broader presentation of
parallel programming with CUDA ranging from CUDA in Cloud and
Cluster environments to CUDA for real problems and applications
helps the reader learning about the unique opportunities this
parallel programming language can offer to the scientific
community. This book is definitely a must for students, teachers,
and developers!" --Michela Taufer, Assistant Professor, Department
of Computer and Information Sciences, University of Delaware
"Rob Farber has written an enlightening and accessible book on the
application to CUDA for real research tasks, with an eye to
developing scalable and distributed GPU applications. He supplies
clear and usable code examples combined with insight about _why_
one should use a particular approach. This is an excellent book
filled with practical advice for experienced CUDA programmers and
ground-up guidance for beginners wondering if CUDA can accelerate
their time to solution." --Paul A. Navrátil, Manager, Visualization
Software, Texas Advanced Computing Center
"The book provides a solid introduction to the CUDA programming
language starting with the basics and progressively exposing the
reader to advanced concepts through the well annotated
implementation of real-world applications. It makes a first-rate
presentation of CUDA, its use in the implementation of portable and
efficient applications and the underlying architecture of GPGPU/CPU
systems with particular emphasis on memory hierarchies. This is
complemented by a thorough presentation both of the CUDA Tool Suite
and of techniques for the parallelisation of applications. Farber's
book is a valuable addition to the bookshelves of both the advanced
and novice CUDA programmer." --Francis Wray, Independent Consultant
and Visiting Professor at the Faculty of Computing, Information
Systems and Mathematics at the University of Kingston
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