Transforming Floating-Point Algorithms to Fixed-Point Implementations: Design Automation for Low-Power Embedded Hardware and Software Implementation of Digital Signal Processing Algorithms

Many digital signal processing and communication algorithms are first simulated using floating-point arithmetic and are later transformed into fixed-point arithmetic to reduce implementation complexity. This transformation process may take most of the design time for complex designs and may involve a long series of manual ad-hoc design choices. This book provides methods to find optimum word lengths efficiently, implement low-power fixed-point arithmetic by word length reduction techniques, and automate the transformation process from floating-point to fixed-point arithmetic. The automation step provides a design tradeoff curve of signal quality vs. implementation complexity for the system, which allows the designer to pick any operating point on the tradeoff curve. The book should help in developing fixed-point hardware or software implementations from floating-point representations, and should be especially useful to professionals who are developing high-speed or low-power hardware or software.

Kyungtae Han is a hardware engineer at Intel Labs. He received his Ph.D. degree from The University of Texas at Austin in electrical engineering. Brian L. Evans is Professor of Electrical and Computer Engineering at The University of Texas at Austin. He received his Ph.D. degree from the Georgia Institute of Technology in electrical engineering.