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Parallel and High Performance Computing

Robert Robey and Yuliana Zamora
  • MEAP began May 2019
  • Publication in June 2021 (estimated)
  • ISBN 9781617296468
  • 704 pages (estimated)
  • printed in black & white

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This is an authoritative, comprehensive and detailed introduction to parallel computing.

Domingo Salazar
Look inside
Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware.

about the technology

Modern computing hardware comes equipped with multicore CPUs and GPUs that can process numerous instruction sets simultaneously. Parallel computing takes advantage of this now-standard computer architecture to execute multiple operations at the same time, offering the potential for applications that run faster, are more energy efficient, and can be scaled to tackle problems that demand large computational capabilities. But to get these benefits, you must change the way you design and write software. Taking advantage of the tools, algorithms, and design patterns created specifically for parallel processing is essential to creating top performing applications.

about the book

Parallel and High Performance Computing is an irreplaceable guide for anyone who needs to maximize application performance and reduce execution time. Parallel computing experts Robert Robey and Yuliana Zamora take a fundamental approach to parallel programming, providing novice practitioners the skills needed to tackle any high-performance computing project with modern CPU and GPU hardware. Get under the hood of parallel computing architecture and learn to evaluate hardware performance, scale up your resources to tackle larger problem sizes, and deliver a level of energy efficiency that makes high performance possible on hand-held devices. When you’re done, you’ll be able to build parallel programs that are reliable, robust, and require minimal code maintenance.

This book is unique in its breadth, with discussions of parallel algorithms, techniques to successfully develop parallel programs, and wide coverage of the most effective languages for the CPU and GPU. The programming paradigms include MPI, OpenMP threading, and vectorization for the CPU. For the GPU, the book covers OpenMP and OpenACC directive-based approaches and the native-based CUDA and OpenCL languages.

what's inside

  • Steps for planning a new parallel project
  • Choosing the right data structures and algorithms
  • Addressing underperforming kernels and loops
  • The differences in CPU and GPU architecture

about the reader

For experienced programmers with proficiency in a high performance computing language such as C, C++, or Fortran.

about the author

Robert Robey has been active in the field of parallel computing for over 30 years. He works at Los Alamos National Laboratory, and has previously worked at the University of New Mexico, where he started up the Albuquerque High Performance Computing Center. Yuliana Zamora has lectured on efficient programming of modern hardware at national conferences, based on her work developing applications running on tens of thousands of processing cores and the latest GPU architectures.

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This is an excellent book and would be invaluable for people new to parallel computing, particularly those working in HPC.

Dana Robinson

Covers both theory and practice and provides tricks to watch for tricks and pitfalls when it comes to developing performance-critical applications.

Arav Kapish Agarwal

Provides deep insights into what it takes to turn a software engineer with only sequential programming knowledge into an expert on parallel programming.

Patrick Regan

A deep and practical book on implementing parallel algorithms. There is no other book at this deep level, working with contemporary systems, that is also so practical in this field.

Phillip G. Bradford

Covers the current state of technology on parallel computing, providing insight on tools and techniques to develop, profile, and test parallel and GPU code.

Albert Choy

Covers both theory and practice and provides tricks to watch for tricks and pitfalls when it comes to developing performance-critical applications.

Jean-François Morin

An extensive overview of the modern Parallel and HPC landscape, in all its facets.

Alain Couniot
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