Biconditional BDD: A Novel Canonical BDD for Logic Synthesis targeting XOR-rich Functions

We present a novel class of decision diagrams, called Biconditional Binary Decision Diagrams (BBDDs), that enable efficient logic synthesis for XOR-rich functions. BBDDs are binary decision diagrams where the Shannon’s expansion is replaced by the biconditional expansion. Since the biconditional expansion is based on the XOR/XNOR operations, XOR-rich logic circuits are efficiently represented and manipulated with canonical Reduced and Ordered BBDDs (ROBBDDs). Experimental results show that ROBBDDs have 37% fewer nodes on average compared to traditional ROBDDs. We exploit this opportunity in logic synthesis for XOR-rich functions. For this purpose, we developed a BBDD- based One-Pass Synthesis (OPS) methodology. The BBDD-based OPS is capable to harness the potential of novel XOR-efficient devices, such as ambipolar transistors. Experimental results show that our logic synthesis methodology reduces the number of ambipolar transistors by 49.7% on average with respect to state-of-art commercial logic synthesis tool. Considering CMOS technology, the BBBD-based OPS reduces the device count by 31.5% on average compared to commercial synthesis tool

Nanowire systems: technology and design (invited paper)

Nanosystems are large-scale integrated systems exploiting nanoelectronic devices. In this work, we consider double independent gate, vertically-stacked nanowire FETs with gate-all-around structures and typical diameter of 20-nm. These devices, which we have successfully fabricated and evaluated, control the ambipolar behavior of the nanostructure by selectively enabling one type of carriers. These transistors work as switches with electrically-programmable polarity and thus realize an exclusive or operation. The intrinsic higher expressive power of these FETs, as compared to standard CMOS, enables us to realize more efficient library cells, which we organize as tiles to realize circuits by regular arrays. This article surveys both the technology for double independent gate FETs as well as physical and logic design tools to realize digital systems with this fabrication technology

Logic synthesis and testing techniques for switching nano-crossbar arrays

Beyond CMOS, new technologies are emerging to extend electronic systems with features unavailable to silicon-based devices. Emerging technologies provide new logic and interconnection structures for computation, storage and communication that may require new design paradigms, and therefore trigger the development of a new generation of design automation tools. In the last decade, several emerging technologies have been proposed and the time has come for studying new ad-hoc techniques and tools for logic synthesis, physical design and testing. The main goal of this project is developing a complete synthesis and optimization methodology for switching nano-crossbar arrays that leads to the design and construction of an emerging nanocomputer. New models for diode, FET, and four-terminal switch based nanoarrays are developed. The proposed methodology implements logic, arithmetic, and memory elements by considering performance parameters such as area, delay, power dissipation, and reliability. With combination of logic, arithmetic, and memory elements a synchronous state machine (SSM), representation of a computer, is realized. The proposed methodology targets variety of emerging technologies including nanowire/nanotube crossbar arrays, magnetic switch-based structures, and crossbar memories. The results of this project will be a foundation of nano-crossbar based circuit design techniques and greatly contribute to the construction of emerging computers beyond CMOS. The topic of this project can be considered under the research area of â\u80\u9cEmerging Computing Modelsâ\u80\u9d or â\u80\u9cComputational Nanoelectronicsâ\u80\u9d, more specifically the design, modeling, and simulation of new nanoscale switches beyond CMOS

Enhancing Logic Synthesis of Switching Lattices by Generalized Shannon Decomposition Methods

In this paper we propose a novel approach to the synthesis of minimal-sized lattices, based on the decomposition of logic functions. Since the decomposition allows to obtain circuits with a smaller area, our idea is to decompose the Boolean functions according to generalizations of the classical Shannon decomposition, then generate the lattices for each component function, and finally implement the original function by a single composed lattice obtained by glueing together appropriately the lattices of the component functions. In particular we study the two decomposition schemes defining the bounded-level logic networks called P-circuits and EXOR-Projected Sums of Products (EP-SOPs). Experimental results show that about 34% of our benchmarks achieve a smaller area when implemented using the P-circuit decomposition for switching lattices, with an average gain of at least 25%, and about 27% of our benchmarks achieve a smaller area when implemented using the EP-SOP decomposition, with an average gain of at least 22%

On the Error Resilience of Ordered Binary Decision Diagrams

Ordered Binary Decision Diagrams (OBDDs) are a data structure that is used in an increasing number of fields of Computer Science (e.g., logic synthesis, program verification, data mining, bioinformatics, and data protection) for representing and manipulating discrete structures and Boolean functions. The purpose of this paper is to study the error resilience of OBDDs and to design a resilient version of this data structure, i.e., a self-repairing OBDD. In particular, we describe some strategies that make reduced ordered OBDDs resilient to errors in the indexes, that are associated to the input variables, or in the pointers (i.e., OBDD edges) of the nodes. These strategies exploit the inherent redundancy of the data structure, as well as the redundancy introduced by its efficient implementations. The solutions we propose allow the exact restoring of the original OBDD and are suitable to be applied to classical software packages for the manipulation of OBDDs currently in use. Another result of the paper is the definition of a new canonical OBDD model, called {\em Index-resilient Reduced OBDD}, which guarantees that a node with a faulty index has a reconstruction cost $O(k)$, where $k$ is the number of nodes with corrupted index

On Decomposing Boolean Functions via Extended Cofactoring

We investigate restructuring techniques based on decomposition/factorization, with the objective to move critical signals toward the output while minimizing area. A specific application is synthesis for minimum switching activity (or high performance), with minimum area penalty, where decompositions with respect to specific critical variables are needed (the ones of highest switching activity for example). In this paper we describe new types of factorization that extend Shannon cofactoring and are based on projection functions that change the Hamming distance of the original minterms and on appropriate don’t care sets, to favor logic minimization of the component blocks. We define two new general forms of decomposition that are special cases of the pattern F = G(H(X),Y). The related implementations, called P-Circuits, show experimentally promising results in area with respect to Shannon cofactoring

On decomposing boolean functions via extended cofactoring

We investigate restructuring techniques based on decomposition/factorization, with the objective to move critical signals toward the output while minimizing area. A specific application is synthesis for minimum switching activity (or high performance), with minimum area penalty, where decompositions with respect to specific critical variables are needed (the ones of highest switching activity for example). In this paper we describe new types of factorization that extend Shannon cofactoring and are based on projection functions that change the Hamming distance of the original minterms and on appropriate don\u2019t care sets, to favor logic minimization of the component blocks. We define two new general forms of decomposition that are special cases of the pattern F = G(H(X),Y). The related implementations, called P-Circuits, show experimentally promising results in area with respect to Shannon cofactoring

DESIGN AND SYNTHESIS OF HIGH DENSITY INTEGRATED CIRCUITS

Gordon E. Moore, a co-founder of Fairchild Semiconductor, and later of Intel, predicted that after 1980 the complexity of an Integrated Circuit would be expected to double every two years. The prevision made by Moore held for decades, for this reason it is also called \u201cMoore\u2019s law\u201d. The trend in ICs is driven by a reduction of area and power consumption. Today scaled CMOS technologies are the main solution for digital processing. However, the interconnection scaling is not optimal. At every new technology node, the number of metal layers and their thickness increases, exploiting the vertical direction. The reduction of the minimum distance between interconnections and the growth in vertical dimension increase the parasitic capacitance and consequently the dynamic power consumption. Moreover, due to the non-optimal scaling of the interconnections, signal routing is becoming more and more challenging at every technology node advancement. Very scaled technologies make possible to reach a great transistor density. However, the design must comply to strict rules for metal interconnections. The aim of this thesis is to find possible solutions to the disadvantages of scaled CMOS technologies. This goal is obtained in two different ways: using ad-hoc design techniques on today CMOS technologies and finding new approaches to logic synthesis of nanocrossbars, that are an emerging post-CMOS technology. The two approaches used corresponds to the two parts of this thesis. The first part presents the design of an Associative Memory focusing the attention on develop design and logic synthesis techniques to reduce power consumption. The field of applicability of AMs is real-time pattern-recognition tasks. The possible uses range from scientific calculations to image processing for intelligent autonomous devices to image reconstruction for electro-medical apparatuses. In particular AMs are used in High Energy Physics (HEP) experiments to detect particle tracks. HEP experiments generate a huge amount of data, but it is necessary to select and save only the most interesting tracks. Being the data compared in parallel, AMs are synchronous ICs that have a very peaked power consumption, and therefore it is necessary to minimize the power consumption. This AM is designed within the projects IMPART and HTT in 28 nm CMOS technology, using a fully-CMOS approach. The logic is based on the propagation of a \u201ckill signal\u201d that, if one of the bits in a word is not matching, inhibits the switching of the following cells. Thanks to this feature, the designed AM array consumes less than 0.7 fJ/bit. A prototype has been fabricated and it has proven to be functional. The final chip will be installed in the data acquisition chain of ATLAS experiment on HL-LHC at CERN. In the future nanocrossbars are expected to reduce device dimensions and interconnection complexity with respect to CMOS. Logic functions are obtained with switching lattices of four-terminal switches. The research activity on nanocrossbars is done within the project NANOxCOMP. To improve synthesis are used some algorithmic approaches based on Boolean function decomposition and regularities, in particular P-circuits, EXOR-Projected Sums of Products (EP-SOP), Dimension-reducible (D-red) functions and autosymmetric functions. The decomposed functions are implemented into lattices using internal and external decomposition methods. Experimental results show that this approaches reduce the complexity of the single synthesis problem and leads, in average, to a reduction of lattice area and synthesis time. Lattices are made of self-assembled structures and they have a non-negligible defectivity ratio. To cope with this limitation, some techniques to reduce sensitivity to defects have been studied