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Books > Computing & IT > Computer hardware & operating systems > Computer architecture & logic design
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Principles of High-Performance Processor Design - For High Performance Computing, Deep Neural Networks and Data Science (Hardcover, 1st ed. 2021)
Loot Price: R4,628
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Principles of High-Performance Processor Design - For High Performance Computing, Deep Neural Networks and Data Science (Hardcover, 1st ed. 2021)
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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.
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