GPU Computing Gems Jade Edition (Applications of GPU Computing Series) - Hardcover

Book 2 of 2: Applications of GPU Computing Series
 
9780123859631: GPU Computing Gems Jade Edition (Applications of GPU Computing Series)

Synopsis

GPU Computing Gems, Jade Edition, offers hands-on, proven techniques for general purpose GPU programming based on the successful application experiences of leading researchers and developers. One of few resources available that distills the best practices of the community of CUDA programmers, this second edition contains 100% new material of interest across industry, including finance, medicine, imaging, engineering, gaming, environmental science, and green computing. It covers new tools and frameworks for productive GPU computing application development and provides immediate benefit to researchers developing improved programming environments for GPUs.

Divided into five sections, this book explains how GPU execution is achieved with algorithm implementation techniques and approaches to data structure layout. More specifically, it considers three general requirements: high level of parallelism, coherent memory access by threads within warps, and coherent control flow within warps. Chapters explore topics such as accelerating database searches; how to leverage the Fermi GPU architecture to further accelerate prefix operations; and GPU implementation of hash tables. There are also discussions on 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. In addition, the book proposes an alternative approach that balances computation regardless of node degree variance.

Software engineers, programmers, hardware engineers, and advanced students will find this book extremely usefull. For useful source codes discussed throughout the book, the editors invite readers to the following website:

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About the Author

Wen-mei W. Hwu
is a Senior Director of
Research of NVIDIA and the
Sanders-AMD Endowed Chair
Professor Emeritus of Electrical
and Computer Engineering
at the University of Illinois
at Urbana-Champaign. His
work focuses on parallel
computing―covering
architecture, implementation,
compilers, and algorithms. Dr.
Hwu has received numerous
honors, including the ACM/
IEEE Eckert-Mauchly Award,
ACM Grace Murray Hopper
Award, IEEE B.R. Rau Award.
He is an IEEE and ACM
Fellow. He earned his Ph.D.
in Computer Science from UC
Berkele

From the Back Cover

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

Features

  • 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

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