학술논문

Improved Linear Decomposition of Majority and Threshold Boolean Functions
Document Type
Periodical
Source
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on. 42(11):3951-3957 Nov, 2023
Subject
Components, Circuits, Devices and Systems
Computing and Processing
Boolean functions
Hamming weight
Complexity theory
Adders
Sorting
Upper bound
Optimization
Circuit synthesis
electronic design automation and methodology
logic circuits
Language
ISSN
0278-0070
1937-4151
Abstract
To support efficient design automation for emerging computing fabrics, novel data structures for logic synthesis and technology mapping are being intensively studied. It has been shown that for several promising computing technologies intermediate forms, such as Majority-inverter graph (MIG) and XOR-Majority graph (XMG) can be particularly beneficial. This has propelled the Boolean Majority operator at the forefront of research. Though these structures primarily utilize 3-input Majority nodes, the efficacy of $n$ -input Majority operators has been demonstrated as well. A long-standing research problem, in that context and also for theoretical circuit complexity, is to determine efficient decomposition of an $n$ -input Majority $({\mathrm{ Maj}}_{n})$ function in terms of 3-input Majority $({\mathrm{ Maj}}_{3})$ operator. In this manuscript, we make two significant advances in this topic. First, a practically realizable linear decomposition is provided, thus improving the previously reported quadratic bounds. Second, the theoretical upper bound of decomposing ${\mathrm{ Maj}}_{n}$ , in terms of ${\mathrm{ Maj}}_{3}$ , is reduced from $5.884n$ to $3n$ . The erstwhile theoretical upper bound of $5.884n$ also lacked a practical construction for ${\mathrm{ Maj}}_{n}$ decomposition, presumably due to the presence of sequential elements in the algorithm. The proof of the linearity, detailed construction procedure along with experimental studies using state-of-the-art synthesis flows to validate the aforementioned claims are presented in this work. The results are applicable to threshold Boolean functions, too.