Programming Massively Parallel Processors discusses basic concepts about parallel programming and GPU architecture. ""Massively parallel"" refers to the use of a large number of processors to perform a set of computations in a coordinated parallel way. The book details various techniques for constructing parallel programs. It also discusses the development process, performance level, floating-point format, parallel patterns, and dynamic parallelism. The book serves as a teaching guide where parallel programming is the main topic of the course. It builds on the basics of C programming for CUDA, a parallel programming environment that is supported on NVI- DIA GPUs. Composed of 12 chapters, the book begins with basic information about the GPU...
AbstractGraphics processor units (GPUs) have evolved to handle throughput oriented workloads where a...
The focus of the training is to understand the basics of accelerator programming with the CUDA paral...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
Through this textbook (written in Spanish), the author introduces the GPU as a parallel computer tha...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
As the computer industry retools to leverage massively parallel graphics processing units (GPUs), th...
GPUs, Graphics Processing Units, offer a large amount of processing power by providing a platform fo...
The goal of the chapter is to introduce the upper-level Computer Engineering/Computer Science underg...
Parallel computing becomes a need to perform task as soon as possible. This can be done in two way i...
The need to speed-up computing has introduced the interest to explore parallelism in algorithms and ...
Academic research and engineering challenge both require high performance computing (HPC), which can...
The future of computation is the GPU, i.e. the Graphical Processing Unit. The graphics cards have sh...
This diploma shows how to solve a compute-intensive problem using a graphics processing unit. Curre...
Graphics Processing Units (GPUs) were originally developed for computer gaming and other graphical t...
AbstractGraphics processor units (GPUs) have evolved to handle throughput oriented workloads where a...
The focus of the training is to understand the basics of accelerator programming with the CUDA paral...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
Through this textbook (written in Spanish), the author introduces the GPU as a parallel computer tha...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
As the computer industry retools to leverage massively parallel graphics processing units (GPUs), th...
GPUs, Graphics Processing Units, offer a large amount of processing power by providing a platform fo...
The goal of the chapter is to introduce the upper-level Computer Engineering/Computer Science underg...
Parallel computing becomes a need to perform task as soon as possible. This can be done in two way i...
The need to speed-up computing has introduced the interest to explore parallelism in algorithms and ...
Academic research and engineering challenge both require high performance computing (HPC), which can...
The future of computation is the GPU, i.e. the Graphical Processing Unit. The graphics cards have sh...
This diploma shows how to solve a compute-intensive problem using a graphics processing unit. Curre...
Graphics Processing Units (GPUs) were originally developed for computer gaming and other graphical t...
AbstractGraphics processor units (GPUs) have evolved to handle throughput oriented workloads where a...
The focus of the training is to understand the basics of accelerator programming with the CUDA paral...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...