Obtain better system performance, lower power consumption, and avoid hand-coding arithmetic functions with this concise guide to automated optimization techniques.
Obtain better system performance, lower power consumption, and avoid hand-coding arithmetic functions with this concise guide to automated optimization techniques.
Ryan Kastner is an Associate Professor in the Department of Computer Science and Engineering at the University of California, San Diego. He received his Ph.D. in Computer Science from UCLA in 2002 and has since published over 90 technical papers and two books. His current research interests are in embedded system design, particularly the use of reconfigurable computing devices for digital signal processing.
Inhaltsangabe
Preface 1. Introduction 2. Use of polynomial expressions and linear systems 3. Software compilation 4. Hardware synthesis 5. Fundamentals of digital arithmetic 6. Polynomial expressions 7. Linear systems.
Preface 1. Introduction 2. Use of polynomial expressions and linear systems 3. Software compilation 4. Hardware synthesis 5. Fundamentals of digital arithmetic 6. Polynomial expressions 7. Linear systems.
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