Overview

Full Product Details

Author:   Jung W. Suh (Senior Algorithm Engineer & Research Scientist, KLA-Tencor) ,  Youngmin Kim (Staff Software Engineer, Life Technologies)
Publisher:   Elsevier Science & Technology
Imprint:   Morgan Kaufmann Publishers In
Dimensions:   Width: 15.10cm , Height: 2.00cm , Length: 22.90cm
Weight:   0.420kg
ISBN:  

9780124080805

ISBN 10:   0124080804
Pages:   258
Publication Date:   17 December 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Preface 1. Accelerating MATLAB without GPU                                                                      2. Configurations for MATLAB and CUDA                                                                 3. Optimization Planning through Profiling 4. CUDA coding with C-MEX 5. MATLAB with Parallel Computing Toolbox 6. Using CUDA-Accelerated Libraries 7. Example in Computer Graphics: 3D Surface Reconstruction using Marching Cubes 8. Example in 3D Image Processing: Atlas-based Segmentation APPENDIX  A.1 Download and install CUDA library  A.2 Installing NVIDIA Nsight into Visual Studio

Reviews

Suh and Kim show graduate students and researchers in engineering, science, and technology how to use a graphics processing unit (GPU) and the NVIDIA company's Compute Unified Device Architecture (CUDA) to process huge amounts of data without losing the many benefits of MATLAB. Readers are assumed to have at least some experience programming MATLAB, but not sufficient background in programming or computer architecture for parallelization. --ProtoView.com, February 2014

Author Information

Jung W. Suh is a senior algorithm engineer and research scientist at KLA-Tencor. Dr. Suh received his Ph.D. from Virginia Tech in 2007 for his 3D medical image processing work. He was involved in the development of MPEG-4 and Digital Mobile Broadcasting (DMB) systems in Samsung Electronics. He was a senior scientist at HeartFlow, Inc., prior to joining KLA-Tencor. His research interests are in the fields of biomedical image processing, pattern recognition, machine learning and image/video compression. He has more than 30 journal and conference papers and 6 patents. Youngmin Kim is a staff software engineer at Life Technologies where he has been programming in the area that requires real-time image acquisition and high-throughput image analysis. His previous works involved designing and developing software for automated microscopy and integrating imaging algorithms for real time analysis. He received his BS and MS from the University of Illinois at Urbana-Champaign in electrical engineering. Since then he developed 3D medical software at Samsung and led a software team at the startup company, prior to joining Life Technologies.

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