CUDA By Example: An Introduction to General-Purpose GPU Programming , authored by NVIDIA’s Jason Sanders and Edward Kandrot, is being published this week by Addison-Wesley Professional.
The book shows how to write high-performance programs that run on the parallel architecture of graphics processing units (GPUs).
NVIDIA (NASDAQ: NVDA), a leading company in visual computing, invented and continues to develop GPUs. NVIDIA launched CUDA in 2006 as a parallel computing architecture that facilitates the use of GPUs for general computation in addition to graphics applications.
Parallel computing is a form of computation in which many calculations are carried out simultaneously. It operates on the principle that large problems can often be divided into smaller ones, which are then solved concurrently. Parallel computing is utilized to address a wide range of computational challenges.Today tens of thousands of developers, scientists and researchers are writing CUDA-based parallel computing applications in areas such as seismic data analysis, financial modeling, medical imaging and weather forecasting, to name a few. Co-authors Sanders and Kandrot build on the reader’s C programming experience by providing an example-driven, quick-start guide to the CUDA C environment (CUDA C is the C programming language with extensions that allow for the programming of massively parallel machines). Book Overview: