As the computer industry retools to leverage massively parallel
graphics processing units (GPUs), this book is designed to meet the
needs of working software developers who need to understand GPU
programming with CUDA and increase efficiency in their projects.
"CUDA Application Design and Development" starts with an
introduction to parallel computing concepts for readers with no
previous parallel experience, and focuses on issues of immediate
importance to working software developers: achieving high
performance, maintaining competitiveness, analyzing CUDA benefits
versus costs, and determining application lifespan.
The book then details the thought behind CUDA and teaches how to
create, analyze, and debug CUDA applications. Throughout, the focus
is on software engineering issues: how to use CUDA in the context
of existing application code, with existing compilers, languages,
software tools, and industry-standard API libraries.
Using an approach refined in a series of well-received articles
at Dr Dobb's Journal, author Rob Farber takes the reader
step-by-step from fundamentals to implementation, moving from
language theory to practical coding.
Includes multiple examples building from simple to more complex
applications in four key areas: machine learning, visualization,
vision recognition, and mobile computingAddresses the foundational
issues for CUDA development: multi-threaded programming and the
different memory hierarchyIncludes teaching chapters designed to
give a full understanding of CUDA tools, techniques and
structure.Presents CUDA techniques in the context of the hardware
they are implemented on as well as other styles of programming that
will help readers bridge into the new material
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