CUDA by Example: An Introduction to General-Purpose GPU Programming

A great deal has been written about the various visions regarding parallel processing. In this dazzle it is often lost to the uninitiated, that parallel computing is not some distant promise, but a revolution that is well in the progress of happening. NVIDIA's CUDA platform is one, and perhaps the easiest and most affordable, of the ways to catch up and to join the front wave of this revolution.CUDA has several components from a hardware architecture for graphics processors to a high level programming interface, implemented as a few extensions to the C language, called CUDA C. One of the main features of the CUDA project is that it makes a systematic effort to separate the programming layer from the chip architecture."CUDA by Example" by Sanders and Kandrot is the first book to make full use of this abstraction and to concentrate solely on the software side. As a result, it is the first text eminently suitable as a basis for an introductory course on CUDA C for students of software engineering or scientific computing. Working through the book the student, or reader, get acquinted step-by-step with most important distinguishing features of parallel programming, like need for memory sharing, event sychronization, atomic operations and isolated processing streams. All this is taught through sofware examples without the need to dwelve into the details of chip architecture. All that is required is some experience in basic C programming and an optional $200-300 "gamer" graphics board to demonstrate the real-life performance gains (no graphics programming experience is required).The authors put a lot of thought into designing each chapter and the corresponding illustrating exaples in such a way that the reader can concentrate on just one new feature at any one time. Every chapter has typically two examples: A very basic one focusing on the newly introduced feature and a more exciting one illustrating some of the power of the new feature. E.g. in the chapter on synchronization, the basic example is provided by the scalar product of two vectors and the need to complete all termwise multiplications before adding up their products. The more dazzling example is a little graphics program, where the lack of proper synchronization manifests itself in the same scrambled screen patterns as what old CRT TV's displayed, when they had synchronization problems. My personal favorite is the very simple heat conduction example, that visually demonstrates the potential of the use of texture memory for spatially related data. It is a gem of simplicity and clarity. (It also captured my fascination because previously I was not able to figure out how to benefit from texture memory in general-purpose applications.)The conscientious choice by the authors to write a software book for software developers implied that hardware dependent tricks had to be omitted. Specifically, code optimizations, that depend on specifics of various generations of chip designs, are not covered. This, as every compromise, has two sides. The positive one is that the knowledge acquired by working through the book will not become outdated, when a new generation of graphics boards hits the market. It also leaves the door open for other potential authors to write a second book on CUDA optimizations.In summary, "CUDA by Example" is an excellent and very welcome introductory text to parallel programming for non-ECE majors. It is very systematic, well tought-out and gradual. It goes beyond demonstrating the ease-of-use and the power of CUDA C; it also introduces the reader to the features and benefits of parallel computing in general. Perhaps a more fitting title could have been "An Introduction to Parallel Programming through CUDA-C Examples". I plan to use this book as the text for the first half of a graduate course on parallel computing for data analysis and quantitative finance.

I read this book a few months ago along with these 2 other books - "Programming Massively Parallel Processors" and "CUDA Application Design and Development" so maybe my review is a bit biased.Pro: (i) Overall, it is a good introductory book. Easy to read. (ii) Good examples, guide the readers step-by-step of what is going on. (iii) Good coverage of some important topics.Con: (i) I agree with another reader here that since this is an introductory text, some instructions of naming the file as *.cu and compile it with nvcc, etc. should be given. Sometimes setting up a development environment could be difficult and/or time-consuming, I for one don't really like to do it. (ii) Snippets of code were introduced first and then the whole program is then reprinted again. IMHO, a bit of re-organization can avoid such problem plus it's a waste of paper. (iii) The pace is a bit slow for me and I think the book could have been shorter.All in all, I would recommend this book to CUDA newbie but keep in mind that some of the topics are already obsolete.

One of the best resources to start with CUDA.Positive aspects from a starting-out perspective: -- a small, very readable book focusing on the important parts to start with; comprehensiveness has it's merits but not when we are just starting out -- brevity does not mean superficialness; the book is very methodical, has examples when you start doing some technique, but alas, it does not improve performance; then it explains more background and help to fix the issue; sticks much better than feeding the conclusion up front -- complete working samples -- enjoyable style; one of the very very small number of books where I am able to appreciate all of the humor (and I'm fussy about this topic; have other reviews triggered by the contrived tiresome attempts to be humorous, which is the case in most tech books I've seen)Will need to read other book(s) after this one but a very good one to start with. Anyone criticizing because of the size is either missing the point or did not get the right book for his own need (through no fault of his own).

This is an excellent introduction to CUDA. The prose and content are excellent: I read it cover-to-cover in a single sitting and enjoyed every page.The authors clearly explain the basic CUDA paradigm starting with very simple code and working up to progressively more complex examples. The authors spend a considerable amount of time discussing different memory types and memory access styles, motivating when each style is appropriate. The code snippets are clean, clear and concise, providing a minimal yet complete introduction to each new language feature.Highly recommended!The book does not provide an HTML pointer to the source code used in the book. Edward Kandrot writes: "The Kindle version shipped a week too soon, it was supposed to ship next week when the physical book ships. Because of this, the website at NVIDIA wasn't done yet. Jason just spent the day making the website happen![...] is where the source code is currently located. I hope this helps. I wrote the examples to be specific for what is being covered, putting extras in the header files so as not to distract from the topic at hand. Only really works if the reader has the header files as well..."

Lo pedí un sábado por la noche y me llego al día siguiente en la mañana.En cuanto al libro, es muy bueno con ejemplos explicados. Te recomiendo que veas un par de vídeos en otros sitios antes de leer el libro para que tengas una idea de lo que es CUDA y depués el libro te explica a fondo.

Todo , era un regalo y acerté

Un ottimo libro per iniziare la tecnologia CUDA: semplice e con esercizi basilari, per imparare la basi del linguaggio di programmazione.

Very well written keeping in view the requirements of beginners in CUDA programming.However, new update or revision of this book as of 2017 is badly needed.

Une bonne publication sur un sujet qui n'est pas facile par des experts venus de chez NvidiaOn peut juste regretter que les sources comporte des spécificités liées au livre.On aurait préféré une approche plus générale dans un premier temps