6 research outputs found

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

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    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

    Biconditional Binary Decision Diagrams: A Novel Canonical Logic Representation Form

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    In this paper, we present biconditional binary deci- sion diagrams (BBDDs), a novel canonical representation form for Boolean functions. BBDDs are binary decision diagrams where the branching condition, and its associated logic expansion, is biconditional on two variables. Empowered by reduction and ordering rules, BBDDs are remarkably compact and unique for a Boolean function. The interest of such representation form in modern electronic design automation (EDA) is twofold. On the one hand, BBDDs improve the efficiency of traditional EDA tasks based on decision diagrams, especially for arithmetic intensive designs. On the other hand, BBDDs represent the natural and native design abstraction for emerging technologies where the circuit primitive is a comparator, rather than a simple switch. We provide, in this paper, a solid ground for BBDDs by studying their underlying theory and manipulation properties. Thanks to an efficient BBDD software package implementation, we validate 1) speed-up in traditional decision diagrams applications with up to 4.4 gain with respect to other DDs, and 2) improved synthesis of circuits in emerging technologies, with about 32% shorter critical path than state-of-art synthesis techniques

    New Data Structures and Algorithms for Logic Synthesis and Verification

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    The strong interaction between Electronic Design Automation (EDA) tools and Complementary Metal-Oxide Semiconductor (CMOS) technology contributed substantially to the advancement of modern digital electronics. The continuous downscaling of CMOS Field Effect Transistor (FET) dimensions enabled the semiconductor industry to fabricate digital systems with higher circuit density at reduced costs. To keep pace with technology, EDA tools are challenged to handle both digital designs with growing functionality and device models of increasing complexity. Nevertheless, whereas the downscaling of CMOS technology is requiring more complex physical design models, the logic abstraction of a transistor as a switch has not changed even with the introduction of 3D FinFET technology. As a consequence, modern EDA tools are fine tuned for CMOS technology and the underlying design methodologies are based on CMOS logic primitives, i.e., negative unate logic functions. While it is clear that CMOS logic primitives will be the ultimate building blocks for digital systems in the next ten years, no evidence is provided that CMOS logic primitives are also the optimal basis for EDA software. In EDA, the efficiency of methods and tools is measured by different metrics such as (i) the result quality, for example the performance of a digital circuit, (ii) the runtime and (iii) the memory footprint on the host computer. With the aim to optimize these metrics, the accordance to a specific logic model is no longer important. Indeed, the key to the success of an EDA technique is the expressive power of the logic primitives handling and solving the problem, which determines the capability to reach better metrics. In this thesis, we investigate new logic primitives for electronic design automation tools. We improve the efficiency of logic representation, manipulation and optimization tasks by taking advantage of majority and biconditional logic primitives. We develop synthesis tools exploiting the majority and biconditional expressiveness. Our tools show strong results as compared to state-of-the-art academic and commercial synthesis tools. Indeed, we produce the best results for several public benchmarks. On top of the enhanced synthesis power, our methods are the natural and native logic abstraction for circuit design in emerging nanotechnologies, where majority and biconditional logic are the primitive gates for physical implementation. We accelerate formal methods by (i) studying properties of logic circuits and (ii) developing new frameworks for logic reasoning engines. We prove non-trivial dualities for the property checking problem in logic circuits. Our findings enable sensible speed-ups in solving circuit satisfiability. We develop an alternative Boolean satisfiability framework based on majority functions. We prove that the general problem is still intractable but we show practical restrictions that can be solved efficiently. Finally, we focus on reversible logic where we propose a new equivalence checking approach. We exploit the invertibility of computation and the functionality of reversible gates in the formulation of the problem. This enables one order of magnitude speed up, as compared to the state-of-the-art solution. We argue that new approaches to solve EDA problems are necessary, as we have reached a point of technology where keeping pace with design goals is tougher than ever

    Linear Sifting of Decision Diagrams

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    We propose a new algorithm, called linear sifting, for the optimization of decision diagrams that combines the efficiency of sifting and the power of linear transformations. We show that the new algorithm is applicable to large examples, and that in many cases it leads to substantially more compact diagrams when compared to simple variable reordering. We show in what sense linear transformations complement variable reordering, andwe discuss applications of the new technique to synthesis and verification
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