Principles of High-Performance Processor Design

For High Performance Computing, Deep Neural Networks and Data Science

Junichiro Makino (Autor)

Buch | Hardcover

XIV, 160 Seiten

2021 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-76870-6 (ISBN)

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This book describes how we can design and make efficient processors for high-performance computing, AI, and data science. Although there are many textbooks on the design of processors we do not have a widely accepted definition of the efficiency of a general-purpose computer architecture. Without a definition of the efficiency, it is difficult to make scientific approach to the processor design. In this book, a clear definition of efficiency is given and thus a scientific approach for processor design is made possible.
In chapter 2, the history of the development of high-performance processor is overviewed, to discuss what quantity we can use to measure the efficiency of these processors. The proposed quantity is the ratio between the minimum possible energy consumption and the actual energy consumption for a given application using a given semiconductor technology. In chapter 3, whether or not this quantity can be used in practice is discussed, for many real-world applications.
In chapter 4, general-purpose processors in the past and present are discussed from this viewpoint. In chapter 5, how we can actually design processors with near-optimal efficiencies is described, and in chapter 6 how we can program such processors. This book gives a new way to look at the field of the design of high-performance processors.

Junichiro Makino received PhD from the University of Tokyo. After he received PhD, he worked at University of Tokyo, the National Astronomical Observatory of Japan, and Tokyo Institute of Technology. Since Apr 2014, he is a subleader of the exascale computing project and the team leader of the Co-design team, AICS, RIKEN, and since Mar 2016 he works also at Kobe University. His research interests are stellar dynamics, large-scale scientific simulation and high-performance computing.
He has developed a series of special-purpose computers for many-body problems (GRAPE) and SIMD many-core processors (GRAPE-DR, MN-Core).

Introduction.- Traditional approaches and their limitations.- The lower limit of energy consumption.- Analysis of past and present processors.- "Near-optimal" designs.- Software.- Present, Past and Future.

Erscheinungsdatum	22.08.2021
Zusatzinfo	XIV, 160 p. 27 illus., 8 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	390 g
Themenwelt	Informatik ► Theorie / Studium ► Algorithmen
Schlagworte	accelerator • Computer Architecture • deep neural networks • energy efficiency • Finite Difference Method • Heterogeneous Multicore Processors • High-Performance Computing • machine learning • Parallel Computing • particle-based method
ISBN-10	3-030-76870-8 / 3030768708
ISBN-13	978-3-030-76870-6 / 9783030768706
Zustand	Neuware