GPU Parallel Program Development Using CUDA, Soyata, Tolga
Автор: Vaidya Bhaumik Название: Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA ISBN: 1789348293 ISBN-13(EAN): 9781789348293 Издательство: Неизвестно Рейтинг: Цена: 10114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a guide to explore how accelerating of computer vision applications using GPUs will help you develop algorithms that work on complex image data in real time. It will solve the problems you face while deploying these algorithms on embedded platforms with the help of development boards from NVIDIA such as the Jetson TX1, Jetson TX2, ...
Автор: Cook, Shane Название: Cuda Programming ISBN: 0124159338 ISBN-13(EAN): 9780124159334 Издательство: Elsevier Science Рейтинг: Цена: 6230.00 р. Наличие на складе: Нет в наличии.
Описание: A guide to CUDA. It features chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. It demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems.
Автор: Tuomanen Dr Brian Название: Hands-On Gpu Programming with Python and Cuda ISBN: 1788993918 ISBN-13(EAN): 9781788993913 Издательство: Неизвестно Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: GPUs are designed for maximum throughput, but are subject to low-level subtleties. In contrast, Python is a high-level language that favours ease of use over speed. In this book, we will combine the power of both Python and CUDA to help you create high performing Python applications by using open-source libraries such as PyCUDA and SciKit-CUDA.
Автор: Matloff, Norman Название: Parallel Computing for Data Science ISBN: 0367738198 ISBN-13(EAN): 9780367738198 Издательство: Taylor&Francis Рейтинг: Цена: 7348.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Matloff, Norman Название: Parallel Computing for Data Science ISBN: 1466587016 ISBN-13(EAN): 9781466587014 Издательство: Taylor&Francis Рейтинг: Цена: 9492.00 р. Наличие на складе: Нет в наличии.
Описание: Discover a variety of data-mining algorithms that are useful for selecting small sets of important features from among unwieldy masses of candidates, or extracting useful features from measured variables.
Автор: Cheng John Название: Professional CUDA C Programming ISBN: 1118739329 ISBN-13(EAN): 9781118739327 Издательство: Wiley Рейтинг: Цена: 7524.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Professional CUDA Programming in C provides down to earth coverage of the complex topic of parallel computing, a topic increasingly essential in every day computing. This entry-level programming book for professionals turns complex subjects into easy-to-comprehend concepts and easy-to-follows steps.
Автор: Masters Название: Deep Belief Nets in C++ and CUDA C: Volume 3 ISBN: 148423720X ISBN-13(EAN): 9781484237205 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications.
At each step Deep Belief Nets in C++ and CUDA C: Volume 3 presents intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the executable CONVNET program which implements these algorithms, are available for free download.
What You Will Learn
Discover convolutional nets and how to use themBuild deep feedforward nets using locally connected layers, pooling layers, and softmax outputsMaster the various programming algorithms requiredCarry out multi-threaded gradient computations and memory allocations for this threadingWork with CUDA code implementations of all core computations, including layer activations and gradient calculationsMake use of the CONVNET program and manual to explore convolutional nets and case studies
Who This Book Is For
Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Автор: Masters Название: Deep Belief Nets in C++ and CUDA C: Volume 2 ISBN: 1484236459 ISBN-13(EAN): 9781484236451 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You'll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C]+ and CUDA C: Volume 2 also covers several algorithms for preprocessing time series and image data. These algorithms focus on the creation of complex-domain predictors that are suitable for input to a complex-domain autoencoder. Finally, you'll learn a method for embedding class information in the input layer of a restricted Boltzmann machine. This facilitates generative display of samples from individual classes rather than the entire data distribution. The ability to see the features that the model has learned for each class separately can be invaluable. At each step this bookprovides you with intuitive motivation, a summary of the most important equations relevant to the topic, and highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. What You'll Learn
Code for deep learning, neural networks, and AI using C++ and CUDA C
Carry out signal preprocessing using simple transformations, Fourier transforms, Morlet wavelets, and more
Use the Fourier Transform for image preprocessing
Implement autoencoding via activation in the complex domain
Work with algorithms for CUDA gradient computation
Use the DEEP operating manual
Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Описание: Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. The first of three in a series on C++ and CUDA C deep learning and belief nets, Deep Belief Nets in C++ and CUDA C: Volume 1 shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a thought process that is capable of learning abstract concepts built from simpler primitives. As such, you'll see that a typical deep belief net can learn to recognize complex patterns by optimizing millions of parameters, yet this model can still be resistant to overfitting. All the routines and algorithms presented in the book are available in the code download, which also contains some libraries of related routines. What You Will Learn
Employ deep learning using C++ and CUDA C
Work with supervised feedforward networks
Implement restricted Boltzmann machines
Use generative samplings
Discover why these are important
Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Автор: Farber, Rob Название: Cuda Application Design And Development ISBN: 0123884268 ISBN-13(EAN): 9780123884268 Издательство: Elsevier Science Рейтинг: Цена: 5893.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: As the computer industry retools to leverage massively parallel graphics processing units (GPUs), this book is designed to meet the needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. It starts with an introduction to parallel computing concepts.
Автор: Bandyopadhyay Avimanyu Название: Hands-On GPU Computing with Python ISBN: 1789341078 ISBN-13(EAN): 9781789341072 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: GPU technologies are the paradigm shift in modern computing. This book will take you through architecting your GPU-based systems to deploying the computational models on GPUs for faster processing. You will learn to program your GPUs to build a GPU-accelerated environment for accelerating machine learning models and other data-intensive processing
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