
This book is intended to present the design of significant scientific
applications on GPUs. Scientific applications require more and more
computational power in a large vaariety of fields: biology, physics,
chemisty, phenomon model and prediction, simulation, mathematics, ...

In order to be able to handle more complex applications, the use of
parallel architectures is the solution to decrease the execution
times of theses applications. Using simulataneously many computing
cores can significantly speed up the processing time.

Nevertheless using parallel architectures is not so easy and has
always required an endeavor to parallelize an application. Nowadays
with general purpose graphics processing units (GPGPU), it is possible
to use either general graphic cards or dedicated graphic cards to benefit from
the computational power of all the cores available inside these
cards. The NVidia company introduced CUDA in 2007 to unify the
programming model to use their video card. CUDA is currently the most
used environment for designing GPU applications although some
alternatives are available, for example OpenCL. According to
applications and the GPU considered, a speed up from 5 up to 50 or even more can be
expected using a GPU instead of computing with a CPU.

The programming model of GPU is quite different from the one of
CPU. It is well adapted to data parallelism applications. Several
books present the CUDA programming models and multi-core applications
design. This book is only focused on scientific applications on GPUs. It
contains 19 chapters gathered in 5 parts.

The first part presents the GPUs. The second part focuses on two
significant image processing applications on GPUs. Part three presents
two general methodologies for software development on GPUs. Part four
describes three optmitization problems on GPUs. The fifth part, the
longuest one, presents 7 numerical applications. Finally part six
illustrates 3 other applications that are not included in the previous
parts.

Some codes presented in this book are available online on my webpage:
http://members.femto-st.fr/raphael-couturier/gpu-book/. 
