This book is for the growing community of scientists and even engineers who use computing and need a scientific understanding of computer architecture – those who view computation as an intellectual multiplier, and consequently are interested in capabilities, scaling, and limits, not mechanisms. That is, the scientific principles behind computer architecture, and how to reason about hardware performance for higher-level ends. With the dramatic rise of both data analytics and artificial intelligence, there has been a rapid growth in interest and progress in data science. There has also been a shift in the center of mass of computer science upward and outward, into a wide variety of sciences (physical, biological, and social), as well as nearly every aspect of society.
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