Heuristic and ILP-Based Optimal Solutions for the Pipelined Multiple Constant Multiplication Problem -- Methods to Integrate Embedded Multipliers, LUT-Based Constant Multipliers and Ternary (3-Input) Adders -- An Optimized Multiple Constant Multiplication Architecture Using Floating Point Arithmetic. .

This work covers field programmable gate array (FPGA)-specific optimizations of circuits computing the multiplication of a variable by several constants, commonly denoted as multiple constant multiplication (MCM). These optimizations focus on low resource usage but high performance. They comprise the use of fast carry-chains in adder-based constant multiplications including ternary (3-input) adders as well as the integration of look-up table-based constant multipliers and embedded multipliers to get the optimal mapping to modern FPGAs. The proposed methods can be used for the efficient implementation of digital filters, discrete transforms and many other circuits in the domain of digital signal processing, communication and image processing. Contents Heuristic and ILP-Based Optimal Solutions for the Pipelined Multiple Constant Multiplication Problem Methods to Integrate Embedded Multipliers, LUT-Based Constant Multipliers and Ternary (3-Input) Adders An Optimized Multiple Constant Multiplication Architecture Using Floating Point Arithmetic Target Groups Researchers and students of electrical engineering and computer science Practitioners in the area of FPGAs and signal processing or digital arithmetic The Author Martin Kumm is working as a postdoctoral researcher at the University of Kassel. His current research interests are digital arithmetic, digital signal processing and discrete optimization, all in the context of field programmable gate arrays. .