GPU computing gems (Record no. 31534)
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| fixed length control field | 09176cam a2200409Ka 4500 |
| 001 - CONTROL NUMBER | |
| control field | 7ocm60175778 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | IE-LiIT |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20180131144725.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS | |
| fixed length control field | m d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr cn||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 111110s2012 mauaf ob 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 0123859638 (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780123859631 (electronic bk.) |
| 037 ## - SOURCE OF ACQUISITION | |
| Stock number | 1107174:11000151 |
| Source of stock number/acquisition | Elsevier Science & Technology |
| Note | http://www.sciencedirect.com |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | OPELS |
| Language of cataloging | eng |
| Transcribing agency | OPELS |
| 245 00 - TITLE STATEMENT | |
| Title | GPU computing gems |
| Medium | [electronic book] / |
| Statement of responsibility, etc. | [edited by] Wen-mei W. Hwu. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | Jade ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Waltham, MA : |
| Name of publisher, distributor, etc. | Morgan Kaufmann, |
| Date of publication, distribution, etc. | c2012. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xvi, 541 p., [16] p. of plates : |
| Other physical details | ill. (some col.) ; |
| Dimensions | 25 cm. |
| 490 0# - SERIES STATEMENT | |
| Series statement | Applications of GPU computing series |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Includes bibliographical references and index. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Part 1: Parallel Algorithms and Data Structures - Paulius Micikevicius, NVIDIA 1 Large-Scale GPU Search 2 Edge v. Node Parallelism for Graph Centrality Metrics 3 Optimizing parallel prefix operations for the Fermi architecture 4 Building an Efficient Hash Table on the GPU 5 An Efficient CUDA Algorithm for the Maximum Network Flow Problem 6 On Improved Memory Access Patterns for Cellular Automata Using CUDA 7 Fast Minimum Spanning Tree Computation on Large Graphs 8 Fast in-place sorting with CUDA based on bitonic sort Part 2: Numerical Algorithms - Frank Jargstorff, NVIDIA 9 Interval Arithmetic in CUDA 10 Approximating the erfinv Function 11 A Hybrid Method for Solving Tridiagonal Systems on the GPU 12 LU Decomposition in CULA 13 GPU Accelerated Derivative-free Optimization Part 3: Engineering Simulation - Peng Wang, NVIDIA 14 Large-scale gas turbine simulations on GPU clusters 15 GPU acceleration of rarefied gas dynamic simulations 16 Assembly of Finite Element Methods on Graphics Processors 17 CUDA implementation of Vertex-Centered, Finite Volume CFD methods on Unstructured Grids with Flow Control Applications 18 Solving Wave Equations on Unstructured Geometries 19 Fast electromagnetic integral equation solvers on graphics processing units (GPUs) Part 4: Interactive Physics for Games and Engineering Simulation - Richard Tonge, NVIDIA 20 Solving Large Multi-Body Dynamics Problems on the GPU 21 Implicit FEM Solver in CUDA 22 Real-time Adaptive GPU multi-agent path planning Part 5: Computational Finance - Thomas Bradley, NVIDIA 23 High performance finite difference PDE solvers on GPUs for financial option pricing 24 Identifying and Mitigating Credit Risk using Large-scale Economic Capital Simulations 25 Financial Market Value-at-Risk Estimation using the Monte Carlo Method Part 6: Programming Tools and Techniques - Cliff Wooley, NVIDIA 26 Thrust: A Productivity-Oriented Library for CUDA 27 GPU Scripting and Code Generation with PyCUDA 28 Jacket: GPU Powered MATLAB Acceleration 29 Accelerating Development and Execution Speed with Just In Time GPU Code Generation 30 GPU Application Development, Debugging, and Performance Tuning with GPU Ocelot 31 Abstraction for AoS and SoA Layout in C++ 32 Processing Device Arrays with C++ Metaprogramming 33 GPU Metaprogramming: A Case Study in Biologically-Inspired Machine Vision 34 A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs 35 Dynamic Load Balancing using Work-Stealing 36 Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads. |
| 505 8# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Machine generated contents note: Part 1: Parallel Algorithms and Data Structures -- Paulius Micikevicius, NVIDIA 1 Large-Scale GPU Search 2 Edge v. Node Parallelism for Graph Centrality Metrics 3 Optimizing parallel prefix operations for the Fermi architecture 4 Building an Efficient Hash Table on the GPU 5 An Efficient CUDA Algorithm for the Maximum Network Flow Problem 6 On Improved Memory Access Patterns for Cellular Automata Using CUDA 7 Fast Minimum Spanning Tree Computation on Large Graphs 8 Fast in-place sorting with CUDA based on bitonic sort Part 2: Numerical Algorithms -- Frank Jargstorff, NVIDIA 9 Interval Arithmetic in CUDA 10 Approximating the erfinv Function 11 A Hybrid Method for Solving Tridiagonal Systems on the GPU 12 LU Decomposition in CULA 13 GPU Accelerated Derivative-free Optimization Part 3: Engineering Simulation -- Peng Wang, NVIDIA 14 Large-scale gas turbine simulations on GPU clusters 15 GPU acceleration of rarefied gas dynamic simulations 16 Assembly of Finite Element Methods on Graphics Processors 17 CUDA implementation of Vertex-Centered, Finite Volume CFD methods on Unstructured Grids with Flow Control Applications 18 Solving Wave Equations on Unstructured Geometries 19 Fast electromagnetic integral equation solvers on graphics processing units (GPUs) Part 4: Interactive Physics for Games and Engineering Simulation -- Richard Tonge, NVIDIA 20 Solving Large Multi-Body Dynamics Problems on the GPU 21 Implicit FEM Solver in CUDA 22 Real-time Adaptive GPU multi-agent path planning Part 5: Computational Finance -- Thomas Bradley, NVIDIA 23 High performance finite difference PDE solvers on GPUs for financial option pricing 24 Identifying and Mitigating Credit Risk using Large-scale Economic Capital Simulations 25 Financial Market Value-at-Risk Estimation using the Monte Carlo Method Part 6: Programming Tools and Techniques -- Cliff Wooley, NVIDIA 26 Thrust: A Productivity-Oriented Library for CUDA 27 GPU Scripting and Code Generation with PyCUDA 28 Jacket: GPU Powered MATLAB Acceleration 29 Accelerating Development and Execution Speed with Just In Time GPU Code Generation 30 GPU Application Development, Debugging, and Performance Tuning with GPU Ocelot 31 Abstraction for AoS and SoA Layout in C++ 32 Processing Device Arrays with C++ Metaprogramming 33 GPU Metaprogramming: A Case Study in Biologically-Inspired Machine Vision 34 A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs 35 Dynamic Load Balancing using Work-Stealing 36 Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This is the second volume of Morgan Kaufmann's GPU Computing Gems, offering an all-new set of insights, ideas, and practical "hands-on" skills from researchers and developers worldwide. Each chapter gives you a window into the work being performed across a variety of application domains, and the opportunity to witness the impact of parallel GPU computing on the efficiency of scientific research. GPU Computing Gems: Jade Edition showcases the latest research solutions with GPGPU and CUDA, including: Improving memory access patterns for cellular automata using CUDA Large-scale gas turbine simulations on GPU clusters Identifying and mitigating credit risk using large-scale economic capital simulations GPU-powered MATLAB acceleration with Jacket Biologically-inspired machine vision An efficient CUDA algorithm for the maximum network flow problem 30 more chapters of innovative GPU computing ideas, written to be accessible to researchers from any industry GPU Computing Gems: Jade Edition contains 100% new material covering a variety of application domains: algorithms and data structures, engineering, interactive physics for games, computational finance, and programming tools. 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | "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"-- |
| Assigning source | Provided by publisher. |
| 533 ## - REPRODUCTION NOTE | |
| Type of reproduction | Electronic reproduction. |
| Place of reproduction | Amsterdam : |
| Agency responsible for reproduction | Elsevier Science & Technology, |
| Date of reproduction | 2011. |
| Note about reproduction | Mode of access: World Wide Web. |
| -- | System requirements: Web browser. |
| -- | Title from title screen (viewed on Nov. 2, 2011). |
| -- | Access may be restricted to users at subscribing institutions. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Graphics processing units |
| General subdivision | Programming. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Imaging systems. |
| 9 (RLIN) | 3468 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Computer graphics. |
| 9 (RLIN) | 1960 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Image processing |
| General subdivision | Digital techniques. |
| 9 (RLIN) | 3463 |
| 655 #7 - INDEX TERM--GENRE/FORM | |
| Genre/form data or focus term | Electronic books. |
| Source of term | local |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Hwu, Wen-mei. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | ScienceDirect (Online service) |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href=" https://www-sciencedirect-com.ezproxy.lit.ie/science/book/9780123859631"> https://www-sciencedirect-com.ezproxy.lit.ie/science/book/9780123859631</a> |
| Link text | ScienceDirect eBook |
| 902 ## - LOCAL DATA ELEMENT B, LDB (RLIN) | |
| a | 120815 |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) | |
| a | .b11427826 |
| b | ebook |
| c | ebook |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Suppress in OPAC | 0 |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 111205 |
| First Date, FD (RLIN) | m |
| Local | @ |
| -- | - |
| -- | 0 |
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