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CUDA by Example

Author : Jason Sanders
Publisher : Addison-Wesley Professional
ISBN 13 : 0132180138
Total Pages : 523 pages
Book Rating : 4.1/5 (321 download)

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Book Synopsis CUDA by Example by : Jason Sanders

Download or read book CUDA by Example written by Jason Sanders and published by Addison-Wesley Professional. This book was released on 2010-07-19 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required—just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA. http://developer.nvidia.com/object/cuda-by-example.html

CUDA Programming

Author : Shane Cook
Publisher : Newnes
ISBN 13 : 0124159338
Total Pages : 592 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis CUDA Programming by : Shane Cook

Download or read book CUDA Programming written by Shane Cook and published by Newnes. This book was released on 2012-11-13 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'CUDA Programming' offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation.

The CUDA Handbook

Author : Nicholas Wilt
Publisher : Addison-Wesley
ISBN 13 : 0133261506
Total Pages : 528 pages
Book Rating : 4.1/5 (332 download)

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Book Synopsis The CUDA Handbook by : Nicholas Wilt

Download or read book The CUDA Handbook written by Nicholas Wilt and published by Addison-Wesley. This book was released on 2013-06-11 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: The CUDA Handbook begins where CUDA by Example (Addison-Wesley, 2011) leaves off, discussing CUDA hardware and software in greater detail and covering both CUDA 5.0 and Kepler. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness. Newer CUDA developers will see how the hardware processes commands and how the driver checks progress; more experienced CUDA developers will appreciate the expert coverage of topics such as the driver API and context migration, as well as the guidance on how best to structure CPU/GPU data interchange and synchronization. The accompanying open source code–more than 25,000 lines of it, freely available at www.cudahandbook.com–is specifically intended to be reused and repurposed by developers. Designed to be both a comprehensive reference and a practical cookbook, the text is divided into the following three parts: Part I, Overview, gives high-level descriptions of the hardware and software that make CUDA possible. Part II, Details, provides thorough descriptions of every aspect of CUDA, including Memory Streams and events Models of execution, including the dynamic parallelism feature, new with CUDA 5.0 and SM 3.5 The streaming multiprocessors, including descriptions of all features through SM 3.5 Programming multiple GPUs Texturing The source code accompanying Part II is presented as reusable microbenchmarks and microdemos, designed to expose specific hardware characteristics or highlight specific use cases. Part III, Select Applications, details specific families of CUDA applications and key parallel algorithms, including Streaming workloads Reduction Parallel prefix sum (Scan) N-body Image Processing These algorithms cover the full range of potential CUDA applications.

GPU Parallel Program Development Using CUDA

Author : Tolga Soyata
Publisher : CRC Press
ISBN 13 : 149875080X
Total Pages : 671 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis GPU Parallel Program Development Using CUDA by : Tolga Soyata

Download or read book GPU Parallel Program Development Using CUDA written by Tolga Soyata and published by CRC Press. This book was released on 2018-01-19 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time, rather than concepts that are platform-specific. At the same time, the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism using CPU multi-threading in Part I. A few simple programs are used to demonstrate the concept of dividing a large task into multiple parallel sub-tasks and mapping them to CPU threads. Multiple ways of parallelizing the same task are analyzed and their pros/cons are studied in terms of both core and memory operation. Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same performance analysis is repeated. Because the core and memory structures of CPUs and GPUs are different, the results differ in interesting ways. The end goal is to make programmers aware of all the good ideas, as well as the bad ideas, so readers can apply the good ideas and avoid the bad ideas in their own programs. Part III of the book provides pointer for readers who want to expand their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS, cuFFT, NPP, and Thrust),the OpenCL programming language, an overview of GPU programming using other programming languages and API libraries (such as Python, OpenCV, OpenGL, and Apple’s Swift and Metal,) and the deep learning library cuDNN.

GPU Programming in MATLAB

Author : Nikolaos Ploskas
Publisher : Morgan Kaufmann
ISBN 13 : 0128051337
Total Pages : 318 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis GPU Programming in MATLAB by : Nikolaos Ploskas

Download or read book GPU Programming in MATLAB written by Nikolaos Ploskas and published by Morgan Kaufmann. This book was released on 2016-08-25 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: GPU programming in MATLAB is intended for scientists, engineers, or students who develop or maintain applications in MATLAB and would like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. The book starts with coverage of the Parallel Computing Toolbox and other MATLAB toolboxes for GPU computing, which allow applications to be ported straightforwardly onto GPUs without extensive knowledge of GPU programming. The next part covers built-in, GPU-enabled features of MATLAB, including options to leverage GPUs across multicore or different computer systems. Finally, advanced material includes CUDA code in MATLAB and optimizing existing GPU applications. Throughout the book, examples and source codes illustrate every concept so that readers can immediately apply them to their own development. Provides in-depth, comprehensive coverage of GPUs with MATLAB, including the parallel computing toolbox and built-in features for other MATLAB toolboxes Explains how to accelerate computationally heavy applications in MATLAB without the need to re-write them in another language Presents case studies illustrating key concepts across multiple fields Includes source code, sample datasets, and lecture slides

Multicore and GPU Programming

Author : Gerassimos Barlas
Publisher : Elsevier
ISBN 13 : 0124171400
Total Pages : 698 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis Multicore and GPU Programming by : Gerassimos Barlas

Download or read book Multicore and GPU Programming written by Gerassimos Barlas and published by Elsevier. This book was released on 2014-12-16 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multicore and GPU Programming offers broad coverage of the key parallel computing skillsets: multicore CPU programming and manycore "massively parallel" computing. Using threads, OpenMP, MPI, and CUDA, it teaches the design and development of software capable of taking advantage of today’s computing platforms incorporating CPU and GPU hardware and explains how to transition from sequential programming to a parallel computing paradigm. Presenting material refined over more than a decade of teaching parallel computing, author Gerassimos Barlas minimizes the challenge with multiple examples, extensive case studies, and full source code. Using this book, you can develop programs that run over distributed memory machines using MPI, create multi-threaded applications with either libraries or directives, write optimized applications that balance the workload between available computing resources, and profile and debug programs targeting multicore machines. Comprehensive coverage of all major multicore programming tools, including threads, OpenMP, MPI, and CUDA Demonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performance Particular focus on the emerging area of divisible load theory and its impact on load balancing and distributed systems Download source code, examples, and instructor support materials on the book's companion website

Programming Massively Parallel Processors

Author : David B. Kirk
Publisher : Newnes
ISBN 13 : 0123914183
Total Pages : 514 pages
Book Rating : 4.1/5 (239 download)

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Book Synopsis Programming Massively Parallel Processors by : David B. Kirk

Download or read book Programming Massively Parallel Processors written by David B. Kirk and published by Newnes. This book was released on 2012-12-31 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing

Parallel and Concurrent Programming in Haskell

Author : Simon Marlow
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449335926
Total Pages : 322 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Parallel and Concurrent Programming in Haskell by : Simon Marlow

Download or read book Parallel and Concurrent Programming in Haskell written by Simon Marlow and published by "O'Reilly Media, Inc.". This book was released on 2013-07-12 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you have a working knowledge of Haskell, this hands-on book shows you how to use the language’s many APIs and frameworks for writing both parallel and concurrent programs. You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions. Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented: Express parallelism in Haskell with the Eval monad and Evaluation Strategies Parallelize ordinary Haskell code with the Par monad Build parallel array-based computations, using the Repa library Use the Accelerate library to run computations directly on the GPU Work with basic interfaces for writing concurrent code Build trees of threads for larger and more complex programs Learn how to build high-speed concurrent network servers Write distributed programs that run on multiple machines in a network

Hands-On GPU Programming with Python and CUDA

Author : Dr. Brian Tuomanen
Publisher : Packt Publishing Ltd
ISBN 13 : 1788995228
Total Pages : 300 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On GPU Programming with Python and CUDA by : Dr. Brian Tuomanen

Download or read book Hands-On GPU Programming with Python and CUDA written by Dr. Brian Tuomanen and published by Packt Publishing Ltd. This book was released on 2018-11-27 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build real-world applications with Python 2.7, CUDA 9, and CUDA 10. We suggest the use of Python 2.7 over Python 3.x, since Python 2.7 has stable support across all the libraries we use in this book. Key FeaturesExpand your background in GPU programming—PyCUDA, scikit-cuda, and NsightEffectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolverApply GPU programming to modern data science applicationsBook Description Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You’ll then see how to “query” the GPU’s features and copy arrays of data to and from the GPU’s own memory. As you make your way through the book, you’ll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You’ll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you’ll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS. With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You’ll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you’ll see some topics and applications related to GPU programming that you may wish to pursue, including AI, graphics, and blockchain. By the end of this book, you will be able to apply GPU programming to problems related to data science and high-performance computing. What you will learnLaunch GPU code directly from PythonWrite effective and efficient GPU kernels and device functionsUse libraries such as cuFFT, cuBLAS, and cuSolverDebug and profile your code with Nsight and Visual ProfilerApply GPU programming to datascience problemsBuild a GPU-based deep neuralnetwork from scratchExplore advanced GPU hardware features, such as warp shufflingWho this book is for Hands-On GPU Programming with Python and CUDA is for developers and data scientists who want to learn the basics of effective GPU programming to improve performance using Python code. You should have an understanding of first-year college or university-level engineering mathematics and physics, and have some experience with Python as well as in any C-based programming language such as C, C++, Go, or Java.

Mastering LLMs and GPUs: A Hands-on Guide to Programming, Optimization, and Deployment

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 71 pages
Book Rating : 4./5 ( download)

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Book Synopsis Mastering LLMs and GPUs: A Hands-on Guide to Programming, Optimization, and Deployment by : Anand Vemula

Download or read book Mastering LLMs and GPUs: A Hands-on Guide to Programming, Optimization, and Deployment written by Anand Vemula and published by Anand Vemula. This book was released on with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tired of slow AI? Want to build groundbreaking applications powered by language? This book is your key! Mastering LLMs and GPUs: A Hands-on Guide to Programming, Optimization, and Deployment equips you with the practical skills to leverage the revolutionary power of Large Language Models (LLMs) and Graphics Processing Units (GPUs). Inside, you'll discover: The Fundamentals: Demystify LLMs, grasp their architectures, and understand how they leverage massive data to generate human-quality text, translate languages, and answer your questions in an informative way. GPU Powerhouse: Unlock the secrets of GPUs, the processing engines that accelerate LLM training compared to traditional CPUs. Learn how to harness their parallel processing capabilities for lightning-fast results. Become an LLM Programming Pro: Code Like a Master: Dive into the world of LLM programming with essential tools and libraries like CUDA or OpenCL. Write code that effectively unleashes the parallel processing power of GPUs. Optimize for Peak Performance: Master memory management strategies to ensure data is readily available for faster processing. Explore techniques for fine-tuning pre-trained LLMs, specializing them for specific tasks and maximizing their effectiveness. Deploy Your LLM Creations: Real-World Applications: Learn to integrate your trained and optimized LLM into applications or cloud platforms, making it accessible for real-world use cases. Practical Considerations: Gain insights into resource management and performance monitoring techniques to keep your LLM running smoothly. Mastering LLMs and GPUs is your comprehensive guide to building powerful language models. With hands-on exercises, clear explanations, and practical advice, you'll be well on your way to developing groundbreaking AI applications that transform the way we interact with language.

Metaprogramming GPUs with Sh

Author : Michael McCool
Publisher : CRC Press
ISBN 13 : 1000730727
Total Pages : 318 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Metaprogramming GPUs with Sh by : Michael McCool

Download or read book Metaprogramming GPUs with Sh written by Michael McCool and published by CRC Press. This book was released on 2009-12-01 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a high-level overview of Sh and its relationship to other realtime shading and Graphics processing unit programming languages. It is a reference manual and language specification and methodically and exhaustively presents details of the various features of Sh.

GPU Gems 2

Author : Matt Pharr
Publisher : Addison-Wesley Professional
ISBN 13 : 9780321335593
Total Pages : 814 pages
Book Rating : 4.3/5 (355 download)

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Book Synopsis GPU Gems 2 by : Matt Pharr

Download or read book GPU Gems 2 written by Matt Pharr and published by Addison-Wesley Professional. This book was released on 2005 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: More useful techniques, tips, and tricks for harnessing the power of the new generation of powerful GPUs.

GPU Zen 2

Author : Wolfgang Engel
Publisher :
ISBN 13 : 9781797583143
Total Pages : 304 pages
Book Rating : 4.5/5 (831 download)

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Book Synopsis GPU Zen 2 by : Wolfgang Engel

Download or read book GPU Zen 2 written by Wolfgang Engel and published by . This book was released on 2019-04-21 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring recent developments in the rapidly evolving field of game real-time rendering, GPU Zen assembles a high-quality collection of cutting-edge contributions for programming the GPU. Rendering (Patrick Cozzi)1. Adaptive GPU Tessellation with Compute Shaders by Jad Khoury, Jonathan Dupuy, and Christophe Riccio2. Applying Vectorized Visibility on All frequency Direct Illumination by Ho Chun Leung, Tze Yui Ho, Zhenni Wang, Chi Sing Leung, Eric Wing Ming Wong3. Non-periodic Tiling of Noise-based Procedural Textures by Aleksandr Kirillov4. Rendering Surgery Simulation with Vulkan by Nicholas Milef, Di Qi, and Suvranu De5. Skinned Decals by Hawar DoghramachiEnvironmental Effects (Wolfgang Engel)1. Real-Time Fluid Simulation in Shadow of the Tomb Raider by Peter Sikachev, Martin Palko and Alexandre Chekroun2. Real-time Snow Deformation in Horizon Zero Dawn: The Frozen Wilds by Kevin ÖrtegrenShadows (Maurizio Vives)1. Soft Shadow Approximation for Dappled Light Sources by Mariano Merchante2. Parallax-Corrected Cached Shadow Maps by Pavlo Turchyn3D Engine Design (Wessam Bahnassi)1. Real-Time Layered Materials Compositing Using Spatial Clustering Encoding by Sergey Makeev2. Procedural Stochastic Textures by Tiling and Blending by Thomas Deliot and Eric Heitz3. A Ray Casting Technique for Baked Texture Generation by Alain Galvan and Jeﬀ Russell4. Writing an efficient Vulkan renderer by Arseny Kapoulkine5. glTF - Runtime 3D Asset Delivery by Marco HutterRay Tracing (Anton Kaplanyan)1. Real-Time Ray-Traced One-Bounce Caustics by Holger Gruen2. Adaptive Anti-Aliasing using Conservative Rasterization and GPU Ray Tracing by Rahul Sathe, Holger Gruen, Adam Marrs, Josef Spjut, Morgan McGuire, Yury Uralsky

Foundations of 3D Graphics Programming

Author : Jim X. Chen
Publisher : Springer Science & Business Media
ISBN 13 : 184800284X
Total Pages : 409 pages
Book Rating : 4.8/5 (48 download)

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Book Synopsis Foundations of 3D Graphics Programming by : Jim X. Chen

Download or read book Foundations of 3D Graphics Programming written by Jim X. Chen and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: OpenGL, which has been bound in C, is a seasoned graphics library for scientists and engineers. As we know, Java is a rapidly growing language becoming the de facto standard of Computer Science learning and application development platform as many undergraduate computer science programs are adopting Java in place of C/C++. Released by Sun Microsystems in June 2003, the recent OpenGL binding with Java, JOGL, provides students, scientists, and engineers a new venue of graphics learning, research, and applications. Overview This book aims to be a shortcut to graphics theory and programming in JOGL. Specifically, it covers OpenGL programming in Java, using JOGL, along with concise computer graphics theories. It covers all graphics basics and several advanced topics without including some implementation details that are not necessary in graphics applications. It also covers some basic concepts in Java programming for C/C++ programmers. It is designed as a textbook for students who know programming basics already. It is an excellent shortcut to learn 3D graphics for scientists and engineers who understand Java programming. It is also a good reference for C/C++ graphics vi Preface programmers to learn Java and JOGL. This book is a companion to Guide to Graphics Software Tools (Springer-Verlag, New York, ISBN 0-387-95049-4), which covers a smaller graphics area with similar examples in C but has a comprehensive list of graphics software tools. Organization and Features This book concisely introduces graphics theory and programming in Java with JOGL.

Programming Your GPU with OpenMP

Author : Tom Deakin
Publisher : MIT Press
ISBN 13 : 0262547538
Total Pages : 332 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Programming Your GPU with OpenMP by : Tom Deakin

Download or read book Programming Your GPU with OpenMP written by Tom Deakin and published by MIT Press. This book was released on 2023-11-07 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential guide for writing portable, parallel programs for GPUs using the OpenMP programming model. Today’s computers are complex, multi-architecture systems: multiple cores in a shared address space, graphics processing units (GPUs), and specialized accelerators. To get the most from these systems, programs must use all these different processors. In Programming Your GPU with OpenMP, Tom Deakin and Timothy Mattson help everyone, from beginners to advanced programmers, learn how to use OpenMP to program a GPU using just a few directives and runtime functions. Then programmers can go further to maximize performance by using CPUs and GPUs in parallel—true heterogeneous programming. And since OpenMP is a portable API, the programs will run on almost any system. Programming Your GPU with OpenMP shares best practices for writing performance portable programs. Key features include: The most up-to-date APIs for programming GPUs with OpenMP with concepts that transfer to other approaches for GPU programming. Written in a tutorial style that embraces active learning, so that readers can make immediate use of what they learn via provided source code. Builds the OpenMP GPU Common Core to get programmers to serious production-level GPU programming as fast as possible. Additional features: A reference guide at the end of the book covering all relevant parts of OpenMP 5.2. An online repository containing source code for the example programs from the book—provided in all languages currently supported by OpenMP: C, C++, and Fortran. Tutorial videos and lecture slides.

GPU Gems 3

Author : Hubert Nguyen
Publisher : Addison-Wesley Professional
ISBN 13 : 9780321515261
Total Pages : 942 pages
Book Rating : 4.5/5 (152 download)

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Book Synopsis GPU Gems 3 by : Hubert Nguyen

Download or read book GPU Gems 3 written by Hubert Nguyen and published by Addison-Wesley Professional. This book was released on 2008 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: Still more useful techniques, tips, and tricks for harnessing the power of the new generation of powerful GPUs.

Hands-On GPU Computing with Python

Author : Avimanyu Bandyopadhyay
Publisher : Packt Publishing Ltd
ISBN 13 : 1789342406
Total Pages : 441 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On GPU Computing with Python by : Avimanyu Bandyopadhyay

Download or read book Hands-On GPU Computing with Python written by Avimanyu Bandyopadhyay and published by Packt Publishing Ltd. This book was released on 2019-05-14 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key FeaturesUnderstand effective synchronization strategies for faster processing using GPUsWrite parallel processing scripts with PyCuda and PyOpenCLLearn to use the CUDA libraries like CuDNN for deep learning on GPUsBook Description GPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you’ll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly. What you will learnUtilize Python libraries and frameworks for GPU accelerationSet up a GPU-enabled programmable machine learning environment on your system with AnacondaDeploy your machine learning system on cloud containers with illustrated examplesExplore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm.Perform data mining tasks with machine learning models on GPUsExtend your knowledge of GPU computing in scientific applicationsWho this book is for Data Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is assumed.