ptg22232966
PRAISE FOR CUDA FOR ENGINEERS
“First there was FORTRAN, circa 1960, which enabled us to program main-
frames. Then there was BASIC, circa 1980, which enabled us to program the
first microcomputers. And now there is CUDA, which enables us to program
super-microcomputers.
“CUDA for Engineers allows researchers in engineering and mathematics to
perform calculations hundreds of times faster than was previously possible on
microcomputers. This permits new kinds of calculations to be performed and
reveals this book to be a game changer.”
— Richard H. Rand, professor of mechanical and aerospace engineering,
and of mathematics, Cornell University
“CUDA for Engineers has been put together in a very thoughtful and practical
way. The reader is quickly immersed in the world of parallel programming with
CUDA and results are seen right away. This book is a great introduction and
helps readers from many different scientific and engineering disciplines become
exposed to the benefits of GPU programming. This book is an enjoyable read and
has great support through top-notch example programs and exercises.”
— Dr. Mark Staveley, senior program manager, Azure High Performance Computing
“CUDA for Engineers lives up to its name by stepping the reader through con-
cepts, strategies, terminology, and examples, which work together to form an
educational framework so that experts and non-experts alike can approach
high- performance computing with foresight and understanding.”
— Joseph M. Iaquinto, Ph.D., research specialist, VA Puget Sound
“This book reflects a practical approach that is in perfect agreement with the
way I teach numerical methods for engineers. It would make a fine supplement
for engineering students or practitioners to add CUDA to their numerical tool-
box, and thus embark on the study of high-performance scientific computing.
It’s perfect for newcomers to CUDA who already have a foundation in program-
ming. I recommend following the authors’ advice and working immediately with
the hands-on exercis es, step by step. After this immersion, you will approach
proficiency by simply adding some personal projects in GPU computing and
delving into the NVIDIA CUDA Guide and developer community.”
— Lorena A. Barba, associate professor of mechanical and aerospace engineering, The
George Washington University
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2018-03-29
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收藏 7.42MB PDF 举报 
generalgaowei2018-05-12值得一读的好书。很清晰，文字版。
commutator_lee2019-04-06非常清晰，非扫描版。
