From: couturie Date: Mon, 20 May 2013 14:22:21 +0000 (+0200) Subject: preface X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/book_gpu.git/commitdiff_plain/ecd2ddac55172a779e7e26d3bd5b1b2cb95033d6 preface --- diff --git a/BookGPU/frontmatter/preface.tex b/BookGPU/frontmatter/preface.tex new file mode 100644 index 0000000..a2bd0f2 --- /dev/null +++ b/BookGPU/frontmatter/preface.tex @@ -0,0 +1,39 @@ + +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/.