GPU Parallel Program Development Using CUDA, Soyata, Tolga
Автор: Newmarch Название: Raspberry Pi GPU Audio Video Programming ISBN: 148422471X ISBN-13(EAN): 9781484224717 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Delve into the Broadcom VideoCore GPU used on the Raspberry Pi and master topics such as OpenGL ES and OpenMAX. Along the way, you’ll also learn some Dispmanx, OpenVG, and GPGPU programming.
The author, Jan Newmarch bumped into a need to do this kind of programming while trying to turn the RPi into a karaoke machine: with the CPU busting its gut rendering MIDI files, there was nothing left for showing images such as karaoke lyrics except for the GPU, and nothing really to tell him how to do it.
Raspberry Pi GPU Audio Video Programming scratches his itch and since he had to learn a lot about RPi GPU programming, he might as well share it with you. What started as a side issue turned into a full-blown project of its own; and this stuff is hard.
What You'll Learn
Use Dispmanx and EGL on Raspberry PiWork with OpenMAX and its components, state, IL Client Library, * * Buffers, and more on RPiProcess images and video on RPiHandle audio on RPiRender OpenMAX to OpenGL on the RPiPlay multimedia files on the RPiUse OpenVG for text processing and moreMaster overlays
Who This Book Is For
You should be comfortable with C programming and at least some concurrency and thread programming using it. This book is for experienced programmers who are new or learning about Raspberry Pi.
Автор: Edvinsson Hakan Название: Enterprise Architecture Made Simple ISBN: 1935504630 ISBN-13(EAN): 9781935504634 Издательство: Gazelle Book Services Рейтинг: Цена: 8792.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Learn how to institute and implement enterprise architecture in your organization. You can make a quick start and establish a baseline for your enterprise architecture within ten weeks, then grow and stabilize the architecture over time using the proven Ready, Set, Go Approach.
Reading this book will:
Give you directions on how to institute and implement enterprise architecture in your organization. You will be able to build close relationships with stakeholders and delivery teams, but you will not need to micromanage the architecture's operations.
Increase your awareness that enterprise architecture is about business, not information technology.
Enable you to initiate and facilitate dramatic business development. The architecture of an enterprise must be tolerant of currently unknown business initiatives.
Show you how to get a holistic view of the process of implementing enterprise architecture.
Make you aware that information is a key business asset and that information architecture is a key part of the enterprise architecture.
Allow you to learn from our experiences. This book is based on our 30 years of work in the enterprise architecture field, colleagues in Europe, customer cases, and students.
We do not pretend to cover all you need to know about enterprise architecture within these pages. Rather, we give you the information that is most important for effective and successful guidance. Sometimes, less is more.
If your company is about to make a major change and you are looking for a way to reduce the changes into manageable pieces--and still retain control of how they fit together--this is your handbook. Maybe you are already acting as an enterprise architect and using a formal method, but you need practical hints. Or maybe you are about to set up an enterprise architect network or group of specialists and need input on how to organize your work.
The Ready-Set-Go method for introducing enterprise architecture provides you, the enterprise architect, with an immediate understanding of the basic steps for starting, organizing, and operating the entirety of your organization's architecture. Chapter 1: Ready shows how to model and analyze your business operations, assess their current status, construct a future scenario, compare it to the current structure, analyze what you see, and show the result in a city plan. Chapter 2: Set deals with preparing for the implementation of the architecture with governance, enterprise architecture organization, staffing, etc. This is the organizing step before beginning the actual work. Chapter 3: Go establishes how to implement a city plan in practice. It deals with the practicalities of working as an enterprise architect and is called the "running" step.
The common thread through all aspects of the enterprise architect's work is the architect's mastery of a number of tools, such as business models, process models, information models, and matrices. We address how to initiate the architecture process within the organization in such a way that the overarching enterprise architecture and architecture-driven approach can be applied methodically and gradually improved.
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: Поставка под заказ.
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: Поставка под заказ.
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 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.
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.
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.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
