Download or read book Performance Analysis and Tuning for General Purpose Graphics Processing Units GPGPU written by Hyesoon Kim and published by Morgan & Claypool Publishers. This book was released on 2012 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Relative to more traditional multicore systems of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques.
Download or read book General Purpose Graphics Processor Architectures written by Tor M. Aamodt and published by Springer Nature. This book was released on 2022-05-31 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally developed to support video games, graphics processor units (GPUs) are now increasingly used for general-purpose (non-graphics) applications ranging from machine learning to mining of cryptographic currencies. GPUs can achieve improved performance and efficiency versus central processing units (CPUs) by dedicating a larger fraction of hardware resources to computation. In addition, their general-purpose programmability makes contemporary GPUs appealing to software developers in comparison to domain-specific accelerators. This book provides an introduction to those interested in studying the architecture of GPUs that support general-purpose computing. It collects together information currently only found among a wide range of disparate sources. The authors led development of the GPGPU-Sim simulator widely used in academic research on GPU architectures. The first chapter of this book describes the basic hardware structure of GPUs and provides a brief overview of their history. Chapter 2 provides a summary of GPU programming models relevant to the rest of the book. Chapter 3 explores the architecture of GPU compute cores. Chapter 4 explores the architecture of the GPU memory system. After describing the architecture of existing systems, Chapters 3 and 4 provide an overview of related research. Chapter 5 summarizes cross-cutting research impacting both the compute core and memory system. This book should provide a valuable resource for those wishing to understand the architecture of graphics processor units (GPUs) used for acceleration of general-purpose applications and to those who want to obtain an introduction to the rapidly growing body of research exploring how to improve the architecture of these GPUs.
Download or read book Graphics Processing Units an Overview written by Patrick Stakem and published by . This book was released on 2017-03-20 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the topic of Graphics Processing Units, which are specialized units found in most modern computer architectures. Although we can do operations of graphics data in regular arithmetic logic units (ALU's), the hardware approach is much faster, Just like for floating pount arithmetic, specialized units speed up the process. We will discuss the applications for GPU's, the data format, and the operations they perform. These specialized units are the backbone to video, and to a large extent audio processing in modern computer architectures. The GPU is a specialized computer architecture, focused on image data manipulation for graphics displays and picture processing. It has applications far that. The normal ALU, Arithmetic-Logic Unit, in a computer does the four basic math operations, and logical operations on integers. These integers are usually 32 or 64 bits at this time. The GPU greatly enhances the spped of 3D graphics. GPU's find application in arcade machines, games consoles, pc's, tablets, phones, car dashboards, tv's and entertainment systems. First, we'll look at the CPU, and the operations it performs on data. The CPU is fairly flexible on what it does, because of software. You can implement a GPU in software, but it won't be very fast. There's a similar co-processor, the floating point unit (FPU) that operates on specially formatted data. You can implement the floating point unit in software, actually, you can probably download the library, but it won't be as fast as using a dedicated piece of hardware. We'll first discuss integer data format, and operations on those data. The "L" part of ALU says we can also do logical (not math) operations on data. GPU's can process integer and floating point data much faster than a cpu, if it is presented in the right format. They don't have all the general purpose features of ALU's, but they can contain 100 cores or more. This has lead to the employment of large numbers of GPU's as the basis for the current generation of Supercomputers.
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 524 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
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.
Download or read book Designing Scientific Applications on GPUs written by Raphael Couturier and published by CRC Press. This book was released on 2013-11-21 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book General Purpose Computing On Graphics Processing Units written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2022-07-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is General Purpose Computing On Graphics Processing Units The term "general-purpose computing on graphics processing units" (also known as "general-purpose computing on GPUs") refers to the practice of employing a graphics processing unit (GPU), which ordinarily performs computation only for the purpose of computer graphics, to carry out computation in programs that are typically performed by the central processing unit (CPU). The already parallel nature of graphics processing may be further parallelized by using numerous video cards in a single computer or a large number of graphics processors. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: General-purpose computing on graphics processing units Chapter 2: Supercomputer Chapter 3: Flynn's taxonomy Chapter 4: Graphics processing unit Chapter 5: Physics processing unit Chapter 6: Hardware acceleration Chapter 7: Stream processing Chapter 8: BrookGPU Chapter 9: CUDA Chapter 10: Close to Metal Chapter 11: Larrabee (microarchitecture) Chapter 12: AMD FireStream Chapter 13: OpenCL Chapter 14: OptiX Chapter 15: Fermi (microarchitecture) Chapter 16: Pascal (microarchitecture) Chapter 17: Single instruction, multiple threads Chapter 18: Multidimensional DSP with GPU Acceleration Chapter 19: Compute kernel Chapter 20: AI accelerator Chapter 21: ROCm (II) Answering the public top questions about general purpose computing on graphics processing units. (III) Real world examples for the usage of general purpose computing on graphics processing units in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of general purpose computing on graphics processing units' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of general purpose computing on graphics processing units.
Download or read book GPU Computing Gems Emerald Edition written by and published by Elsevier. This book was released on 2011-01-13 with total page 889 pages. Available in PDF, EPUB and Kindle. Book excerpt: GPU Computing Gems Emerald Edition offers practical techniques in parallel computing using graphics processing units (GPUs) to enhance scientific research. The first volume in Morgan Kaufmann's Applications of GPU Computing Series, this book offers the latest insights and research in computer vision, electronic design automation, and emerging data-intensive applications. It also covers life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing. This book is intended to help those who are facing the challenge of programming systems to effectively use GPUs to achieve efficiency and performance goals. It offers developers a window into diverse application areas, and the opportunity to gain insights from others' algorithm work that they may apply to their own projects. Readers will learn from the leading researchers in parallel programming, who have gathered their solutions and experience in one volume under the guidance of expert area editors. Each chapter is written to be accessible to researchers from other domains, allowing knowledge to cross-pollinate across the GPU spectrum. Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution. The insights and ideas as well as practical hands-on skills in the book can be immediately put to use. Computer programmers, software engineers, hardware engineers, and computer science students will find this volume a helpful resource. For useful source codes discussed throughout the book, the editors invite readers to the following website: ..." Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and more Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution Offers insights and ideas as well as practical "hands-on" skills you can immediately put to use
Download or read book GPU Computing Gems Jade Edition written by Wen-mei Hwu and published by Elsevier. This book was released on 2011-09-28 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--
Download or read book CUDA Handbook written by Nicholas Wilt and published by Addison-Wesley. This book was released on 2013-06-11 with total page 526 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.
Download or read book Graphics Processing Unit Based High Performance Computing in Radiation Therapy written by Xun Jia and published by CRC Press. This book was released on 2018-09-21 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use the GPU Successfully in Your Radiotherapy Practice With its high processing power, cost-effectiveness, and easy deployment, access, and maintenance, the graphics processing unit (GPU) has increasingly been used to tackle problems in the medical physics field, ranging from computed tomography reconstruction to Monte Carlo radiation transport simulation. Graphics Processing Unit-Based High Performance Computing in Radiation Therapy collects state-of-the-art research on GPU computing and its applications to medical physics problems in radiation therapy. Tackle Problems in Medical Imaging and Radiotherapy The book first offers an introduction to the GPU technology and its current applications in radiotherapy. Most of the remaining chapters discuss a specific application of a GPU in a key radiotherapy problem. These chapters summarize advances and present technical details and insightful discussions on the use of GPU in addressing the problems. The book also examines two real systems developed with GPU as a core component to accomplish important clinical tasks in modern radiotherapy. Translate Research Developments to Clinical Practice Written by a team of international experts in radiation oncology, biomedical imaging, computing, and physics, this book gets clinical and research physicists, graduate students, and other scientists up to date on the latest in GPU computing for radiotherapy. It encourages you to bring this novel technology to routine clinical radiotherapy practice.
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.
Download or read book Cuda by Example written by Jason Sanders and published by Createspace Independent Publishing Platform. This book was released on 2017-07-14 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: GPUs can be used for much more than graphics processing. As opposed to a CPU, which can only run four or five threads at once, a GPU is made up of hundreds or even thousands of individual, low-powered cores, allowing it to perform thousands of concurrent operations. Because of this, GPUs can tackle large, complex problems on a much shorter time scale than CPUs. Dive into parallel programming on NVIDIA hardware with CUDA by Chris Rose, and learn the basics of unlocking your graphics card. This updated and expanded second edition of Book provides a user-friendly introduction to the subject, Taking a clear structural framework, it guides the reader through the subject's core elements. A flowing writing style combines with the use of illustrations and diagrams throughout the text to ensure the reader understands even the most complex of concepts. This succinct and enlightening overview is a required reading for all those interested in the subject . We hope you find this book useful in shaping your future career & Business.
Download or read book Parallel and High Performance Computing written by Robert Robey and published by Simon and Schuster. This book was released on 2021-08-24 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. Summary Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. About the technology Write fast, powerful, energy efficient programs that scale to tackle huge volumes of data. Using parallel programming, your code spreads data processing tasks across multiple CPUs for radically better performance. With a little help, you can create software that maximizes both speed and efficiency. About the book Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. You’ll learn to evaluate hardware architectures and work with industry standard tools such as OpenMP and MPI. You’ll master the data structures and algorithms best suited for high performance computing and learn techniques that save energy on handheld devices. You’ll even run a massive tsunami simulation across a bank of GPUs. What's inside Planning a new parallel project Understanding differences in CPU and GPU architecture Addressing underperforming kernels and loops Managing applications with batch scheduling About the reader For experienced programmers proficient with a high-performance computing language like C, C++, or Fortran. About the author Robert Robey works at Los Alamos National Laboratory and has been active in the field of parallel computing for over 30 years. Yuliana Zamora is currently a PhD student and Siebel Scholar at the University of Chicago, and has lectured on programming modern hardware at numerous national conferences. Table of Contents PART 1 INTRODUCTION TO PARALLEL COMPUTING 1 Why parallel computing? 2 Planning for parallelization 3 Performance limits and profiling 4 Data design and performance models 5 Parallel algorithms and patterns PART 2 CPU: THE PARALLEL WORKHORSE 6 Vectorization: FLOPs for free 7 OpenMP that performs 8 MPI: The parallel backbone PART 3 GPUS: BUILT TO ACCELERATE 9 GPU architectures and concepts 10 GPU programming model 11 Directive-based GPU programming 12 GPU languages: Getting down to basics 13 GPU profiling and tools PART 4 HIGH PERFORMANCE COMPUTING ECOSYSTEMS 14 Affinity: Truce with the kernel 15 Batch schedulers: Bringing order to chaos 16 File operations for a parallel world 17 Tools and resources for better code
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.
Download or read book CUDA Application Design and Development written by Rob Farber and published by Elsevier. This book was released on 2011-10-31 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries."--Pub. desc.
Download or read book GPU Based Interactive Visualization Techniques written by Daniel Weiskopf and published by Springer Science & Business Media. This book was released on 2006-10-13 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents efficient visualization techniques, a prerequisite for the interactive exploration of complex data sets. High performance is demonstrated as a process of devising algorithms for the fast graphics processing units (GPUs) of modern graphics hardware. Coverage includes parallelization on cluster computers with several GPUs, adaptive rendering methods, and non-photorealistic rendering techniques for visualization.
