Build GPU-accelerated high performing applications with Python 2.7, CUDA 9, and open source libraries such as PyCUDA and scikit-cuda. We recommend the use of Python 2.7 as this version has stable support across all libraries used in this book.
Among the many configuration management tools available, Ansible has some distinct advantages—it’s minimal in nature, you don’t need to install anything on your nodes, and it has an easy learning curve. This practical guide shows you how to be productive with this tool quickly, whether you’re a developer...
Write algorithms and program in the new field of quantum computing. This book covers major topics such as the physical components of a quantum computer: qubits, entanglement, logic gates, circuits, and how they differ from a traditional computer. Also, Practical Quantum Computing for Developers...
In the decade since the publication of the first edition of “Explorations in Quantum Computing” the field has blossomed into a rich and diverse body of knowledge, and tremendous progress has been made on building functional quantum computer hardware. Yet I find that a discussion of applications of quantum computers still remains...
GPU Pro4: Advanced Rendering Techniques presents ready-to-use ideas and procedures that can help solve many of your day-to-day graphics programming challenges. Focusing on interactive media and games, the book covers up-to-date methods for producing real-time graphics.
