Books: 13

GPU

CoverTitleYear
The Hardware Software Interface
The new ARM Edition of Computer Organization and Design features a subset of the ARMv8-A architecture, which is used to present the fundamentals of hardware technologies, assembly language, computer arithmetic, pipelining, memory hierarchies, and I/O. With the post-PC era now upon us, Computer Organization more » and Design moves forward to explore this generational change with examples, exercises, and material highlighting the emergence of mobile computing and the Cloud. Updated content featuring tablet computers, Cloud infrastructure, and the ARM (mobile computing devices) and x86 (cloud computing) architectures is included. An online companion Web site provides links to a free version of the DS-5 Community Edition (a free professional quality tool chain developed by ARM), as well as additional advanced content for further study, appendices, glossary, references, and recommended reading. * Covers parallelism in depth with examples and content highlighting parallel hardware and software topics * Features the Intel Core i7, ARM Cortex-A53, and NVIDIA Fermi GPU as real-world examples throughout the book * Adds a new concrete example, "Going Faster," to demonstrate how understanding hardware can inspire software optimizations that improve performance by 200X * Discusses and highlights the "Eight Great Ideas" of computer architecture: Performance via Parallelism; Performance via Pipelining; Performance via Prediction; Design for Moore's Law; Hierarchy of Memories; Abstraction to Simplify Design; Make the Common Case Fast; and Dependability via Redundancy. * Includes a full set of updated exercises « less
2016
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 more » 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 « less
2016
Prevalent types of data in scientific visualization are volumetric data, vector field data, and particle-based data. Particle data typically originates from measurements and simulations in various fields, such as life sciences or physics. The particles are often visualized directly, that is, by simple more » representants like spheres. Interactive rendering facilitates the exploration and visual analysis of the data. With increasing data set sizes in terms of particle numbers, interactive high-quality visualization is a challenging task. This is especially true for dynamic data or abstract representations that are based on the raw particle data. This book covers direct particle visualization using simple glyphs as well as abstractions that are application-driven such as clustering and aggregation. It targets visualization researchers and developers who are interested in visualization techniques for large, dynamic particle-based data. Its explanations focus on GPU-accelerated algorithms for high-performance rendering and data processing that run in real-time on modern desktop hardware. Consequently, the implementation of said algorithms and the required data structures to make use of the capabilities of modern graphics APIs are discussed in detail. Furthermore, it covers GPU-accelerated methods for the generation of application-dependent abstract representations. This includes various representations commonly used in application areas such as structural biology, systems biology, thermodynamics, and astrophysics. « less
2016
The Official Guide to Learning Vulkan (OpenGL)
The Definitive Vulkan™ Developer’s Guide and Reference: Master the Next-Generation Specification for Cross-Platform Graphics The next generation of the OpenGL specification, Vulkan, has been redesigned from the ground up, giving applications direct control over GPU acceleration for unprecedented performance more » and predictability. Vulkan™ Programming Guide is the essential, authoritative reference to this new standard for experienced graphics programmers in all Vulkan environments. Vulkan API lead Graham Sellers (with contributions from language lead John Kessenich) presents example-rich introductions to the portable Vulkan API and the new SPIR-V shading language. The author introduces Vulkan, its goals, and the key concepts framing its API, and presents a complex rendering system that demonstrates both Vulkan’s uniqueness and its exceptional power. You’ll find authoritative coverage of topics ranging from drawing to memory, and threading to compute shaders. The author especially shows how to handle tasks such as synchronization, scheduling, and memory management that are now the developer’s responsibility. Vulkan™ Programming Guide introduces powerful 3D development techniques for fields ranging from video games to medical imaging, and state-of-the-art approaches to solving challenging scientific compute problems. Whether you’re upgrading from OpenGL or moving to open-standard graphics APIs for the first time, this guide will help you get the results and performance you’re looking for. Coverage includes * Extensively tested code examples to demonstrate Vulkan’s capabilities and show how it differs from OpenGL * Expert guidance on getting started and working with Vulkan’s new memory system * Thorough discussion of queues, commands, moving data, and presentation * Full explanations of the SPIR-V binary shading language and compute/graphics pipelines * Detailed discussions of drawing commands, geometry and fragment processing, synchronization primitives, and reading Vulkan data into applications * A complete case study application: deferred rendering using complex multi-pass architecture and multiple processing queues * Appendixes presenting Vulkan functions and SPIR-V opcodes, as well as a complete Vulkan glossary « less
2016
1001 tips to speed up MATLAB programs
The MATLAB® programming environment is often perceived as a platform suitable for prototyping and modeling but not for "serious" applications. One of the main complaints is that MATLAB is just too slow. Accelerating MATLAB Performance aims to correct this perception by describing multiple ways to more » greatly improve MATLAB program speed. Packed with thousands of helpful tips, it leaves no stone unturned, discussing every aspect of MATLAB. Ideal for novices and professionals alike, the book describes MATLAB performance in a scale and depth never before published. It takes a comprehensive approach to MATLAB performance, illustrating numerous ways to attain the desired speedup. The book covers MATLAB, CPU, and memory profiling and discusses various tradeoffs in performance tuning. It describes both the application of standard industry techniques in MATLAB, as well as methods that are specific to MATLAB such as using different data types or built-in functions. The book covers MATLAB vectorization, parallelization (implicit and explicit), optimization, memory management, chunking, and caching. It explains MATLAB’s memory model and details how it can be leveraged. It describes the use of GPU, MEX, FPGA, and other forms of compiled code, as well as techniques for speeding up deployed applications. It details specific tips for MATLAB GUI, graphics, and I/O. It also reviews a wide variety of utilities, libraries, and toolboxes that can help to improve performance. Sufficient information is provided to allow readers to immediately apply the suggestions to their own MATLAB programs. Extensive references are also included to allow those who wish to expand the treatment of a particular topic to do so easily. Supported by an active website, and numerous code examples, the book will help readers rapidly attain significant reductions in development costs and program run times. « less
2014
Selected Papers from ADBIS 2013 Satellite Events
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development more » in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This special issue contains extended and revised versions of 4 papers, selected from the 25 papers presented at the satellite events associated with the 17th East-European Conference on Advances in Databases and Information Systems (ADBIS 2013), held on September 1-4, 2013 in Genoa, Italy. The three satellite events were GID 2013, the Second International Workshop on GPUs in Databases; SoBI 2013, the First International Workshop on Social Business Intelligence: Integrating Social Content in Decision Making; and OAIS 2013, the Second International Workshop on Ontologies Meet Advanced Information Systems. The papers cover various topics in large-scale data and knowledge-centered systems, including GPU-accelerated database systems and GPU-based compression for large time series databases, design of parallel data warehouses, and schema matching. The special issue content, which combines both theoretical and application-based contributions, gives a useful overview of some of the current trends in large-scale data and knowledge management and will stimulate new ideas for further research and development within both the scientific and industrial communities. « less
2014
A Primer with Examples
Beyond simulation and algorithm development, many developers increasingly use MATLAB even for product deployment in computationally heavy fields. This often demands that MATLAB codes run faster by leveraging the distributed parallelism of Graphics Processing Units (GPUs). While MATLAB successfully provides more » high-level functions as a simulation tool for rapid prototyping, the underlying details and knowledge needed for utilizing GPUs make MATLAB users hesitate to step into it. Accelerating MATLAB with GPUs offers a primer on bridging this gap. Starting with the basics, setting up MATLAB for CUDA (in Windows, Linux and Mac OS X) and profiling, it then guides users through advanced topics such as CUDA libraries. The authors share their experience developing algorithms using MATLAB, C++ and GPUs for huge datasets, modifying MATLAB codes to better utilize the computational power of GPUs, and integrating them into commercial software products. Throughout the book, they demonstrate many example codes that can be used as templates of C-MEX and CUDA codes for readers’ projects. Download example codes from the publisher's website: http://booksite.elsevier.com/9780124080805/ * Shows how to accelerate MATLAB codes through the GPU for parallel processing, with minimal hardware knowledge * Explains the related background on hardware, architecture and programming for ease of use * Provides simple worked examples of MATLAB and CUDA C codes as well as templates that can be reused in real-world projects « less
2013
Algorithms and Applications
This book presents the state of the art in parallel numerical algorithms, applications, architectures, and system software. The book examines various solutions for issues of concurrency, scale, energy efficiency, and programmability, which are discussed in the context of a diverse range of applications. more » Features: includes contributions from an international selection of world-class authorities; examines parallel algorithm-architecture interaction through issues of computational capacity-based codesign and automatic restructuring of programs using compilation techniques; reviews emerging applications of numerical methods in information retrieval and data mining; discusses the latest issues in dense and sparse matrix computations for modern high-performance systems, multicores, manycores and GPUs, and several perspectives on the Spike family of algorithms for solving linear systems; presents outstanding challenges and developing technologies, and puts these in their historical context. « less
2012
"...the perfect companion to Programming Massively Parallel Processors by Hwu & Kirk." -Nicolas Pinto, Research Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010 Graphics processing units (GPUs) can do much more than render graphics. Scientists and researchers increasingly look to GPUs to more » improve the efficiency and performance of computationally-intensive experiments across a range of disciplines. GPU Computing Gems: Emerald Edition brings their techniques to you, showcasing GPU-based solutions including: * Black hole simulations with CUDA * GPU-accelerated computation and interactive display of molecular orbitals * Temporal data mining for neuroscience * GPU -based parallelization for fast circuit optimization * Fast graph cuts for computer vision * Real-time stereo on GPGPU using progressive multi-resolution adaptive windows * GPU image demosaicing * Tomographic image reconstruction from unordered lines with CUDA * Medical image processing using GPU -accelerated ITK image filters * 41 more chapters of innovative GPU computing ideas, written to be accessible to researchers from any domain GPU Computing Gems: Emerald Edition is the first volume in Morgan Kaufmann's Applications of GPU Computing Series, offering the latest insights and research in computer vision, electronic design automation, emerging data-intensive applications, life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, and video / image processing. * 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 « less
2011
GPU Computing Gems, Jade Edition describes successful application experiences in GPU computing and the techniques that contributed to that success. Divided into five sections, the book explains how GPU execution is achieved with algorithm implementation techniques and approaches to data structure layout. more » More specifically, it considers three general requirements: high level of parallelism, coherent memory access by threads within warps, and coherent control flow within warps. This book begins with an overview of parallel algorithms and data structures. The first few chapters focus on accelerating database searches, how to leverage the Fermi GPU architecture to further accelerate prefix operations, and GPU implementation of hash tables. The reader is then systematically walked through the fundamental optimization steps when implementing a bandwidth-limited algorithm, GPU-based libraries of numerical algorithms and software products for numerical analysis with dedicated GPU support, and the adoption of GPU computing techniques in production engineering simulation codes. The next chapters discuss the state of GPU computing in interactive physics and artificial intelligence, programming tools and techniques for GPU computing, and the edge and node parallelism approach for computing graph centrality metrics. The book also proposes an alternative approach that balances computation regardless of node degree variance. This book will be useful to application developers in a wide range of application areas. * This second volume of GPU Computing Gems offers 100% new material of interest across industry, including finance, medicine, imaging, engineering, gaming, environmental science, green computing, and more * Covers new tools and frameworks for productive GPU computing application development and offers immediate benefit to researchers developing improved programming environments for GPUs * Even more hands-on, proven techniques demonstrating how general purpose GPU computing is changing scientific research * Distills the best practices of the community of CUDA programmers; each chapter provides insights and ideas as well as 'hands on' skills applicable to a variety of fields « less
2011