Programming Massively Parallel Processors: A Hands-on Approach - Softcover

Hwu, Wen-mei W.; Kirk, David B.; El Hajj, Izzat

Softcover

ISBN 10: 0323912311 ISBN 13: 9780323912310

Publisher: Morgan Kaufmann, 2022

Synopsis

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
  

About this title

About the Authors

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

David B. Kirk
is known for major
contributions to graphics,
hardware, and algorithms.
Before pursuing his Ph.D. at
Caltech, he earned B.S. and
M.S. degrees in mechanical
engineering from MIT and
worked at Raster Technologies
and Hewlett-Packard’s Apollo
Systems Division. After
completing his doctorate, he
served as chief scientist and
head of technology at Crystal
Dynamics. In 1997, he became
Chief Scientist at NVIDIA. Dr.
Kirk has received numerous
honors including the IEEE
Seymour Cray Computer
Engineering Award and
ACM SIGGRAPH Computer
Graphics Achievement
Award. He is a member of
the U.S. National Academy of
Engineering.

Izzat El Hajj
is an Assistant Professor
of Computer Science at
the American University
of Beirut. His research
focuses on leveraging
accelerator architectures
to tackle challenging
computations, with a
focus on GPU computing,
processing-in-memory,
and performance
modeling. He earned his
Ph.D. in Electrical and
Computer Engineering at
the University of Illinois
at Urbana-Champaign.
He has received the
Dan Vivoli Endowed
Fellowship (UIUC) and the
Distinguished Graduate
Award from the American
University of Beirut.

From the Back Cover

Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. For this new edition, the authors are updating their coverage of CUDA, including the concept of unified memory, and expanding content in areas such as threads, while still retaining its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses.

Edition details

• Publisher: Morgan Kaufmann
• Publication date: 2022
• Language: English
• ISBN 10: 0323912311
• ISBN 13: 9780323912310
• Binding: Paperback
• Edition number: 4
• Number of pages: 580