Programming Massively Parallel Processors

Programming Massively Parallel Processors PDF Author: Wen-mei W. Hwu
Publisher: Morgan Kaufmann
ISBN: 0323984630
Category : Computers
Languages : en
Pages : 581

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Book Description
Programming Massively Parallel Processors: A Hands-on Approach shows both students and professionals alike the basic concepts of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel computing courses. Various techniques for constructing and optimizing parallel programs are explored in detail, while case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. The new edition includes updated coverage of CUDA, including the newer libraries such as CuDNN. New chapters on frequently used parallel patterns have been added, and case studies have been updated to reflect current industry practices. - Parallel Patterns Introduces new chapters on frequently used parallel patterns (stencil, reduction, sorting) and major improvements to previous chapters (convolution, histogram, sparse matrices, graph traversal, deep learning) - Ampere Includes a new chapter focused on GPU architecture and draws examples from recent architecture generations, including Ampere - Systematic Approach Incorporates major improvements to abstract discussions of problem decomposition strategies and performance considerations, with a new optimization checklist

Programming Massively Parallel Processors

Programming Massively Parallel Processors PDF Author: Wen-mei W. Hwu
Publisher: Morgan Kaufmann
ISBN: 0323984630
Category : Computers
Languages : en
Pages : 581

Get Book Here

Book Description
Programming Massively Parallel Processors: A Hands-on Approach shows both students and professionals alike the basic concepts of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel computing courses. Various techniques for constructing and optimizing parallel programs are explored in detail, while case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. The new edition includes updated coverage of CUDA, including the newer libraries such as CuDNN. New chapters on frequently used parallel patterns have been added, and case studies have been updated to reflect current industry practices. - Parallel Patterns Introduces new chapters on frequently used parallel patterns (stencil, reduction, sorting) and major improvements to previous chapters (convolution, histogram, sparse matrices, graph traversal, deep learning) - Ampere Includes a new chapter focused on GPU architecture and draws examples from recent architecture generations, including Ampere - Systematic Approach Incorporates major improvements to abstract discussions of problem decomposition strategies and performance considerations, with a new optimization checklist

GPU Computing Gems Emerald Edition

GPU Computing Gems Emerald Edition PDF Author:
Publisher: Elsevier
ISBN: 0123849896
Category : Computers
Languages : en
Pages : 889

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Book Description
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

Programming Massively Parallel Processors

Programming Massively Parallel Processors PDF Author: David B. Kirk
Publisher: Newnes
ISBN: 0123914183
Category : Computers
Languages : en
Pages : 519

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Book Description
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

Fundamentals of Computerized Tomography

Fundamentals of Computerized Tomography PDF Author: Gabor T. Herman
Publisher: Springer Science & Business Media
ISBN: 1846287235
Category : Computers
Languages : en
Pages : 302

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Book Description
This revised and updated second edition – now with two new chapters - is the only book to give a comprehensive overview of computer algorithms for image reconstruction. It covers the fundamentals of computerized tomography, including all the computational and mathematical procedures underlying data collection, image reconstruction and image display. Among the new topics covered are: spiral CT, fully 3D positron emission tomography, the linogram mode of backprojection, and state of the art 3D imaging results. It also includes two new chapters on comparative statistical evaluation of the 2D reconstruction algorithms and alternative approaches to image reconstruction.

Computational Methods for Molecular Imaging

Computational Methods for Molecular Imaging PDF Author: Fei Gao
Publisher: Springer
ISBN: 3319184318
Category : Technology & Engineering
Languages : en
Pages : 203

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Book Description
This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to: • Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities • Molecular Imaging Enhancement • Data Analysis of Clinical & Pre-clinical Molecular Imaging • Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.) • Machine Learning and Data Mining in Molecular Imaging. Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization. This work will bring readers from academia and industry up to date on the most recent developments in this field.

Clinical PET-CT in Radiology

Clinical PET-CT in Radiology PDF Author: Paul Shreve
Publisher: Springer Science & Business Media
ISBN: 0387489029
Category : Medical
Languages : en
Pages : 432

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Book Description
This book is specifically designed to meet the needs of practicing radiologists by offering a practical, unified approach to PET-CT. It details how to effectively apply PET-CT in patient management. Written by radiologists who fully appreciate and understand both PET and CT, the book details an integrated understanding of PET-CT as a combined modality. Clinical topics include PET-CT of thoracic malignancies, melanoma, and breast cancer. In addition, the book reinforces fundamental concepts, such as the role of imaging diagnosis in disease management.

Medical Image Reconstruction

Medical Image Reconstruction PDF Author: Gengsheng Zeng
Publisher: Springer Science & Business Media
ISBN: 3642053688
Category : Technology & Engineering
Languages : en
Pages : 204

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Book Description
"Medical Image Reconstruction: A Conceptual Tutorial" introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l0-minimization are also included. This book is written for engineers and researchers in the field of biomedical engineering specializing in medical imaging and image processing with image reconstruction. Gengsheng Lawrence Zeng is an expert in the development of medical image reconstruction algorithms and is a professor at the Department of Radiology, University of Utah, Salt Lake City, Utah, USA.

High-Performance Modelling and Simulation for Big Data Applications

High-Performance Modelling and Simulation for Big Data Applications PDF Author: Joanna Kołodziej
Publisher: Springer
ISBN: 3030162729
Category : Computers
Languages : en
Pages : 364

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Book Description
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.

Distributed and Cloud Computing

Distributed and Cloud Computing PDF Author: Kai Hwang
Publisher: Morgan Kaufmann
ISBN: 0128002042
Category : Computers
Languages : en
Pages : 671

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Book Description
Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. - Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing - Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more - Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery - Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online

Recent Trends in Image Processing and Pattern Recognition

Recent Trends in Image Processing and Pattern Recognition PDF Author: K. C. Santosh
Publisher: Springer
ISBN: 9811391815
Category : Computers
Languages : en
Pages : 744

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Book Description
This three-volume set constitutes the refereed proceedings of the Second International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2018, held in Solapur, India, in December 2018. The 173 revised full papers presented were carefully reviewed and selected from 374 submissions. The papers are organized in topical sections in the tree volumes. Part I: computer vision and pattern recognition; machine learning and applications; and image processing. Part II: healthcare and medical imaging; biometrics and applications. Part III: document image analysis; image analysis in agriculture; and data mining, information retrieval and applications.