The CUDA Handbook

A Comprehensive Guide to GPU Programming

Author: Nicholas Wilt

Publisher: Addison-Wesley

ISBN: 0133261506

Category: Computers

Page: 528

View: 1461

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.

The CUDA Handbook

A Comprehensive Guide to GPU Programming

Author: Nicholas Wilt

Publisher: Pearson Education

ISBN: 0321809467

Category: Computers

Page: 494

View: 2132

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.

The Cuda Handbook

A Comprehensive Guide to Gpu Programming

Author: Nicholas Wilt

Publisher: Addison-Wesley Professional

ISBN: 9780134852744

Category: Computers

Page: 528

View: 3787

The CUDA Handbook is the only comprehensive reference to CUDA that exists. 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 30,000 lines of it, freely available from github -- is specifically intended to be reused and repurposed by developers.

CUDA by Example

An Introduction to General-Purpose GPU Programming, Portable Documents

Author: Jason Sanders,Edward Kandrot

Publisher: Addison-Wesley Professional

ISBN: 0132180138

Category: Computers

Page: 312

View: 424

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

A Developer's Guide to Parallel Computing with GPUs

Author: Shane Cook

Publisher: Newnes

ISBN: 0124159338

Category: Computers

Page: 576

View: 7369

If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction 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. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems. Comprehensive introduction to parallel programming with CUDA, for readers new to both Detailed instructions help readers optimize the CUDA software development kit Practical techniques illustrate working with memory, threads, algorithms, resources, and more Covers CUDA on multiple hardware platforms: Mac, Linux and Windows with several NVIDIA chipsets Each chapter includes exercises to test reader knowledge

Professional CUDA C Programming

Author: John Cheng,Max Grossman,Ty McKercher

Publisher: John Wiley & Sons

ISBN: 1118739329

Category: Computers

Page: 528

View: 6608

OpenCL Programming Guide

Author: Aaftab Munshi,Benedict Gaster,Timothy G. Mattson,Dan Ginsburg

Publisher: Pearson Education

ISBN: 9780132594554

Category: Computers

Page: 648

View: 7039

Using the new OpenCL (Open Computing Language) standard, you can write applications that access all available programming resources: CPUs, GPUs, and other processors such as DSPs and the Cell/B.E. processor. Already implemented by Apple, AMD, Intel, IBM, NVIDIA, and other leaders, OpenCL has outstanding potential for PCs, servers, handheld/embedded devices, high performance computing, and even cloud systems. This is the first comprehensive, authoritative, and practical guide to OpenCL 1.1 specifically for working developers and software architects. Written by five leading OpenCL authorities, OpenCL Programming Guide covers the entire specification. It reviews key use cases, shows how OpenCL can express a wide range of parallel algorithms, and offers complete reference material on both the API and OpenCL C programming language. Through complete case studies and downloadable code examples, the authors show how to write complex parallel programs that decompose workloads across many different devices. They also present all the essentials of OpenCL software performance optimization, including probing and adapting to hardware. Coverage includes Understanding OpenCL’s architecture, concepts, terminology, goals, and rationale Programming with OpenCL C and the runtime API Using buffers, sub-buffers, images, samplers, and events Sharing and synchronizing data with OpenGL and Microsoft’s Direct3D Simplifying development with the C++ Wrapper API Using OpenCL Embedded Profiles to support devices ranging from cellphones to supercomputer nodes Case studies dealing with physics simulation; image and signal processing, such as image histograms, edge detection filters, Fast Fourier Transforms, and optical flow; math libraries, such as matrix multiplication and high-performance sparse matrix multiplication; and more Source code for this book is available at https://code.google.com/p/opencl-book-samples/

CUDA Application Design and Development

Author: Rob Farber

Publisher: Elsevier

ISBN: 0123884268

Category: Computers

Page: 315

View: 8681

Machine generated contents note: 1. How to think in CUDA 2. Tools to build, debug and profile 3. The GPU performance envelope 4. The CUDA memory subsystems 5. Exploiting the CUDA execution grid 6. MultiGPU applications and scaling 7. Numerical CUDA, libraries and high-level language bindings 8. Mixing CUDA with rendering 9. High Performance Machine Learning 10. Scientific Visualization 11. Multimedia with OpenCV 12. Ultra Low-power Devices: Tegra.

CUDA for Engineers

An Introduction to High-Performance Parallel Computing

Author: Duane Storti,Mete Yurtoglu

Publisher: Addison-Wesley Professional

ISBN: 013417755X

Category: Computers

Page: 352

View: 2543

CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you’ll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA’s parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debugging Creating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA’s shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations

Programming Massively Parallel Processors

A Hands-on Approach

Author: David B. Kirk,Wen-mei W. Hwu

Publisher: Morgan Kaufmann

ISBN: 012811987X

Category: Computers

Page: 576

View: 3818

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices. Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing Utilizes CUDA version 7.5, NVIDIA's software development tool created specifically for massively parallel environments Contains new and updated case studies Includes coverage of newer libraries, such as CuDNN for Deep Learning

GPU Parallel Program Development Using CUDA

Author: Tolga Soyata

Publisher: CRC Press

ISBN: 1498750761

Category: Mathematics

Page: 440

View: 1727

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.

Designing Scientific Applications on GPUs

Author: Raphael Couturier

Publisher: CRC Press

ISBN: 1466571640

Category: Mathematics

Page: 498

View: 7133

Many of today’s complex scientific applications now require a vast amount of computational power. General purpose graphics processing units (GPGPUs) enable researchers in a variety of fields to benefit from the computational power of all the cores available inside graphics cards. Understand the Benefits of Using GPUs for Many Scientific Applications Designing Scientific Applications on GPUs shows you how to use GPUs for applications in diverse scientific fields, from physics and mathematics to computer science. The book explains the methods necessary for designing or porting your scientific application on GPUs. It will improve your knowledge about image processing, numerical applications, methodology to design efficient applications, optimization methods, and much more. Everything You Need to Design/Port Your Scientific Application on GPUs The first part of the book introduces the GPUs and Nvidia’s CUDA programming model, currently the most widespread environment for designing GPU applications. The second part focuses on significant image processing applications on GPUs. The third part presents general methodologies for software development on GPUs and the fourth part describes the use of GPUs for addressing several optimization problems. The fifth part covers many numerical applications, including obstacle problems, fluid simulation, and atomic physics models. The last part illustrates agent-based simulations, pseudorandom number generation, and the solution of large sparse linear systems for integer factorization. Some of the codes presented in the book are available online.

Numerical Computations with GPUs

Author: Volodymyr Kindratenko

Publisher: Springer

ISBN: 3319065483

Category: Computers

Page: 405

View: 2926

This book brings together research on numerical methods adapted for Graphics Processing Units (GPUs). It explains recent efforts to adapt classic numerical methods, including solution of linear equations and FFT, for massively parallel GPU architectures. This volume consolidates recent research and adaptations, covering widely used methods that are at the core of many scientific and engineering computations. Each chapter is written by authors working on a specific group of methods; these leading experts provide mathematical background, parallel algorithms and implementation details leading to reusable, adaptable and scalable code fragments. This book also serves as a GPU implementation manual for many numerical algorithms, sharing tips on GPUs that can increase application efficiency. The valuable insights into parallelization strategies for GPUs are supplemented by ready-to-use code fragments. Numerical Computations with GPUs targets professionals and researchers working in high performance computing and GPU programming. Advanced-level students focused on computer science and mathematics will also find this book useful as secondary text book or reference.

CUDA Fortran for Scientists and Engineers

Best Practices for Efficient CUDA Fortran Programming

Author: Gregory Ruetsch,Massimiliano Fatica

Publisher: Elsevier

ISBN: 0124169724

Category: Computers

Page: 338

View: 2277

CUDA Fortran for Scientists and Engineers shows how high-performance application developers can leverage the power of GPUs using Fortran, the familiar language of scientific computing and supercomputer performance benchmarking. The authors presume no prior parallel computing experience, and cover the basics along with best practices for efficient GPU computing using CUDA Fortran. To help you add CUDA Fortran to existing Fortran codes, the book explains how to understand the target GPU architecture, identify computationally intensive parts of the code, and modify the code to manage the data and parallelism and optimize performance. All of this is done in Fortran, without having to rewrite in another language. Each concept is illustrated with actual examples so you can immediately evaluate the performance of your code in comparison. Leverage the power of GPU computing with PGI’s CUDA Fortran compiler Gain insights from members of the CUDA Fortran language development team Includes multi-GPU programming in CUDA Fortran, covering both peer-to-peer and message passing interface (MPI) approaches Includes full source code for all the examples and several case studies Download source code and slides from the book's companion website

GPU Computing Gems

Author: Wen-mei W. Hwu

Publisher: Elsevier

ISBN: 0123859638

Category: Computers

Page: 541

View: 2205

"Since the introduction of CUDA in 2007, more than 100 million computers with CUDA capable GPUs have been shipped to end users. GPU computing application developers can now expect their application to have a mass market. With the introduction of OpenCL in 2010, researchers can now expect to develop GPU applications that can run on hardware from multiple vendors"--

Talent Force

A New Manifesto for the Human Side of Business

Author: Hank Stringer,Rusty Rueff

Publisher: Pearson Education

ISBN: 0132704056

Category: Business & Economics

Page: 224

View: 1636

Only one thing really differentiates your business from your competitor: your people. Do you have the right talent in the right place at the right time? It's no longer enough to have a 'workforce': you need a high-impact Talent Force. The authors first identify the massive social, cultural, and economic shifts that are transforming hiring as we know it. We are a smaller, closer, and more competitive world, as Baby Boomers are retiring in the US, India is flourishing due to outsourcing and educational development, and China is a strong new economic force. Add to that the fact that today's best people have radically new expectations and approaches to work; this book reveals what they want and how to meet those needs while building your business. Learn how to develop and implement a worldclass talent plan that aligns with business objectives, and define metrics to track and optimize success. Discover how candidates are using technology to evaluate new opportunities, benchmark compensation, and create new back-channels of communication about worklife. Maximize these new technologies to grow Talent Force, tap into new sources of competitive intelligence and stay ahead of the pack. Foreword xi Acknowledgments xiii About the Authors xv Preface xvii Introduction xix Chapter 1: The Quality Talent Imperative 1 Chapter 2: Talent Market Demands 11 Chapter 3: Building a Competitive Talent Organization 35 Chapter 4: The Cultural Obsession of Work 59 Chapter 5: Building a Talent Community 77 Chapter 6: Tangible Talent Measurement 93 Chapter 7: Talent Goes on Offense 115 Chapter 8: Relationship Recruiting (Still) Rules 133 Chapter 9: Talent Forces of Tomorrow 151 Index 163

Multicore Application Programming

For Windows, Linux, and Oracle Solaris

Author: Darryl Gove

Publisher: Addison-Wesley Professional

ISBN: 0321711378

Category: Computers

Page: 441

View: 4012

Multicore Application Programming is a comprehensive, practical guide to high-performance multicore programming that any experienced developer can use. Author Darryl Gove covers the leanding approaches to parallelization on Windows, Linux, and Oracle Solaris. Through practical examples, he illuminates the challenges involved in writing applications that fully utilize multicore processors, helping you produce appllications that are functionally correct, offer superior performance, and scale well to eight cores, sixteen Cores, and beyond. The book reveals how specific hardware implementations impact application performance and shows how to avoid common pitfalls. Step by step, you'll write applications that can handle large numbers of parallel threads, and you'll master advanced parallelization techniques. Multicore Application Programming isn't wedded to a single approach or platform: It is for every experienced C programmer working with any contemporary multicore processor in any leading operating system environment.

A Field Guide to Genetic Programming

Author: N.A

Publisher: Lulu.com

ISBN: 1409200736

Category: Computers

Page: 233

View: 7825

Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until high-fitness solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org.uk for more information on the book.

Playing with Sound

A Theory of Interacting with Sound and Music in Video Games

Author: Karen Collins

Publisher: MIT Press

ISBN: 0262312301

Category: Games

Page: 200

View: 6317

In Playing with Sound, Karen Collins examines video game sound from the player's perspective. She explores the many ways that players interact with a game's sonic aspects -- which include not only music but also sound effects, ambient sound, dialogue, and interface sounds -- both within and outside of the game. She investigates the ways that meaning is found, embodied, created, evoked, hacked, remixed, negotiated, and renegotiated by players in the space of interactive sound in games. Drawing on disciplines that range from film studies and philosophy to psychology and computer science, Collins develops a theory of interactive sound experience that distinguishes between interacting with sound and simply listening without interacting. Her conceptual approach combines practice theory (which focuses on productive and consumptive practices around media) and embodied cognition (which holds that our understanding of the world is shaped by our physical interaction with it). Collins investigates the multimodal experience of sound, image, and touch in games; the role of interactive sound in creating an emotional experience through immersion and identification with the game character; the ways in which sound acts as a mediator for a variety of performative activities; and embodied interactions with sound beyond the game, including machinima, chip-tunes, circuit bending, and other practices that use elements from games in sonic performances.

Programming with POSIX Threads

Author: David R. Butenhof

Publisher: Addison-Wesley Professional

ISBN: 9780201633924

Category: Computers

Page: 381

View: 6316

Threads are the key to faster, more efficient, and easier-to-maintain operating systems. Butenhof, a recognized authority on POSIX threads, tells how to use Pthreads in the real world, making efficient and portable applications. A unique feature of the book is the many examples which consist of simple instructive programs. The code is expansive and well-annotated. Key chapters are devoted to advanced threaded programming, real code (including read-write locks), and hints to avoid bad code and performance problems. Programming in POSIX Threads provides a solid general understanding of threaded programming models, concurrency, synchronization, and scheduling--need to know information for learning to think in terms of threaded concepts.