programming massively parallel processors third edition a hands on approach

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Programming Massively Parallel Processors

Author : David B. Kirk
ISBN : 9780128119877
Genre : Computers
File Size : 35. 57 MB
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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

Programming Massively Parallel Processors

Author : David B. Kirk
ISBN : 9780123914187
Genre : Computers
File Size : 67. 73 MB
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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

Programming Massively Parallel Processors

Author : David B. Kirk
ISBN : 0123814731
Genre : Computers
File Size : 43. 77 MB
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Programming Massively Parallel Processors discusses the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This book describes computational thinking techniques that will enable students to think about problems in ways that are amenable to high-performance parallel computing. It utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for massively parallel environments. Studies learn how to achieve both high-performance and high-reliability using the CUDA programming model as well as OpenCL. This book is recommended for advanced students, software engineers, programmers, and hardware engineers. Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing. Utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for massively parallel environments. Shows you how to achieve both high-performance and high-reliability using the CUDA programming model as well as OpenCL.

Cuda Application Design And Development

Author : Rob Farber
ISBN : 9780123884268
Genre : Computers
File Size : 33. 95 MB
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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 Programming

Author : Shane Cook
ISBN : 9780124159334
Genre : Computers
File Size : 63. 63 MB
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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

The Cuda Handbook

Author : Nicholas Wilt
ISBN : 9780133261509
Genre : Computers
File Size : 74. 77 MB
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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.

Intel Xeon Phi Coprocessor High Performance Programming

Author : James Jeffers
ISBN : 9780124104945
Genre : Computers
File Size : 25. 47 MB
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Authors Jim Jeffers and James Reinders spent two years helping educate customers about the prototype and pre-production hardware before Intel introduced the first Intel Xeon Phi coprocessor. They have distilled their own experiences coupled with insights from many expert customers, Intel Field Engineers, Application Engineers and Technical Consulting Engineers, to create this authoritative first book on the essentials of programming for this new architecture and these new products. This book is useful even before you ever touch a system with an Intel Xeon Phi coprocessor. To ensure that your applications run at maximum efficiency, the authors emphasize key techniques for programming any modern parallel computing system whether based on Intel Xeon processors, Intel Xeon Phi coprocessors, or other high performance microprocessors. Applying these techniques will generally increase your program performance on any system, and better prepare you for Intel Xeon Phi coprocessors and the Intel MIC architecture. A practical guide to the essentials of the Intel Xeon Phi coprocessor Presents best practices for portable, high-performance computing and a familiar and proven threaded, scalar-vector programming model Includes simple but informative code examples that explain the unique aspects of this new highly parallel and high performance computational product Covers wide vectors, many cores, many threads and high bandwidth cache/memory architecture

Gpu Computing Gems

Author : Wen-mei W. Hwu
ISBN : 9780123859631
Genre : Computers
File Size : 28. 32 MB
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"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"--

Heterogeneous System Architecture

Author : Wen-mei W. Hwu
ISBN : 9780128008010
Genre : Computers
File Size : 31. 26 MB
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Heterogeneous Systems Architecture - a new compute platform infrastructure presents a next-generation hardware platform, and associated software, that allows processors of different types to work efficiently and cooperatively in shared memory from a single source program. HSA also defines a virtual ISA for parallel routines or kernels, which is vendor and ISA independent thus enabling single source programs to execute across any HSA compliant heterogeneous processer from those used in smartphones to supercomputers. The book begins with an overview of the evolution of heterogeneous parallel processing, associated problems, and how they are overcome with HSA. Later chapters provide a deeper perspective on topics such as the runtime, memory model, queuing, context switching, the architected queuing language, simulators, and tool chains. Finally, three real world examples are presented, which provide an early demonstration of how HSA can deliver significantly higher performance thru C++ based applications. Contributing authors are HSA Foundation members who are experts from both academia and industry. Some of these distinguished authors are listed here in alphabetical order: Yeh-Ching Chung, Benedict R. Gaster, Juan Gómez-Luna, Derek Hower, Lee Howes, Shih-Hao HungThomas B. Jablin, David Kaeli,Phil Rogers, Ben Sander, I-Jui (Ray) Sung. Provides clear and concise explanations of key HSA concepts and fundamentals by expert HSA Specification contributors Explains how performance-bound programming algorithms and application types can be significantly optimized by utilizing HSA hardware and software features Presents HSA simply, clearly, and concisely without reading the detailed HSA Specification documents Demonstrates ideal mapping of processing resources from CPUs to many other heterogeneous processors that comply with HSA Specifications

Multicore And Gpu Programming

Author : Gerassimos Barlas
ISBN : 9780124171404
Genre : Computers
File Size : 61. 37 MB
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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

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