Programming HTML5 Applications

CUDA is now the dominant language used for programming GPUs, one of the most exciting hardware developments of recent decades. With CUDA, you can use a desktop PC for work that would have previously required a large cluster of PCs or access to a HPC facility. As a result, CUDA is increasingly important in scientific and technical computing across the whole STEM community, from medical physics and financial modelling to big data applications and beyond. This unique book on CUDA draws on the author's passion for and long experience of developing and using computers to acquire and analyse scientific data. The result is an innovative text featuring a much richer set of examples than found in any other comparable book on GPU computing. Much attention has been paid to the C++ coding style, which is compact, elegant and efficient. A code base of examples and supporting material is available online, which readers can build on for their own projects.

Thistitle is a Pearson Global Edition. The editorial team at Pearson has workedclosely with educators around the world to include content which is especiallyrelevant to an international and diverse audience.For courses in computerprogramming.A user-friendly,code-intensive introduction to C programming with case studies introducing applicationsand system programming.C How to Program is a comprehensive introduction toprogramming in C. Like other texts of the Deitels How to Program series,the books modular presentation serves as a detailed, beginner source ofinformation for college students looking to embark on a career in coding, orinstructors and software-development professionals seeking to learn how toprogram with C. The signature Deitel live-code approach presents concepts inthe context of 142 fully working programs rather than incomplete snips of code.This gives students a chance to run each program as they study it and see howtheir learning applies to real-world programming scenari

What does a probabilistic program actually compute? How can one formally reason about such probabilistic programs? This valuable guide covers such elementary questions and more. It provides a state-of-the-art overview of the theoretical underpinnings of modern probabilistic programming and their applications in machine learning, security, and other domains, at a level suitable for graduate students and non-experts in the field. In addition, the book treats the connection between probabilistic programs and mathematical logic, security (what is the probability that software leaks confidential information?), and presents three programming languages for different applications: Excel tables, program testing, and approximate computing. This title is also available as Open Access on Cambridge Core.