Adiabatic superconducting devices are promising candidates to develop high-speed/low-power electronics. Advances in physical technology must be matched with a systematic development of comprehensive design and simulation tools to bring superconducting electronics to a commercially viable state. Being the technology fundamentally different from CMOS, new challenges are posed to design automation tools: library cells are controlled by multi-phase clocks, they implement the majority logic function, and they have limited fanout. We present a product-level RTL-to-GDSII flow for the design of Adiabatic Quantum-Flux-Parametron (AQFP) electronic circuits, with a focus on the special techniques used to comply with these challenges. In addition, we demonstrate new optimization opportunities for graph matching, resynthesis, and buffer/splitter insertion, improving the state-of-the-art.

Look-up Table (LUT) mapping and optimization is an important step in Field Programmable Gate Arrays (FPGAs) design. The effectiveness of LUT synthesis improved dramatically in the last decades, thanks to optimization and mapping innovations naturally tailored for FPGAs. In this paper, we develop a new LUT-based optimization flow that is tailored for the synthesis of Application-Specific Integrated Circuits (ASICs) rather than FPGAs. We enhance LUT mapping to consider the literal/AIG cost of LUT nodes. We extend traditional Boolean methods to simplify and re-shape LUT-networks, targeting the best AIG/mapped-network implementation, after decomposition. Intuitively, literal-driven LUT packing behaves as a powerful fanin-bound node elimination, unveiling higher-order Boolean simplification opportunities. We embed our proposed LUT-based optimization flow, area oriented, in a commercial synthesis tool. Using our methodology, we improve 12 of the best area results in the EPFL synthesis competition. Employed in a commercial EDA flow for ASICs, our LUT optimization reduces area by 1.80%, total negative slack by 0.39%, and switching power by 1.72%, after physical implementation, at 5% runtime cost.

SAT-sweeping is a powerful method for simplifying logic networks. It consists of merging gates that are proven equivalent (up to complementation) by running simulation and SAT solving in synergy. SAT-sweeping is used in both verification and synthesis applications within EDA. In this paper, we focus on the development of a highly efficient, synthesis-oriented, SAT-sweeping engine. We introduce a new algorithm to guide initial simulation, which strongly reduces the number of false candidates for merge, thus increasing the computational efficiency of the sweeper. We revisit the SAT-sweeping flow in light of practical considerations for synthesis, with the aim of proving all valid merges and ensuring fast execution. Experimental results confirm remarkable speedup deriving from our methodology, up to 10× for large combinational networks, and better QoR as compared to previous SAT-sweeping implementation. Embedded in a commercial synthesis flow, our proposes SAT-sweeper enables area and power savings of 1.98% and 1.81%, respectively, with neutral timing at negligible runtime overhead, over 36 testcases.

Combinational equivalence checking (CEC) has been widely applied to ensure design correctness after logic synthesis and technology-dependent optimization in digital integrated circuit design. CEC runtime is often critical for large designs, even when advanced techniques are employed. Three complementary ways for enabling parallelism in CEC are proposed, addressing different design and verification scenarios. The experimental results have demonstrated the speedups up to 63x when comparing the proposed approach to a single-threaded implementation of a similar CEC engine. A practical impact of such a speedup, for instance, is the runtime reduction from 19 h to only 18 min when checking equivalence of AND-inverter graphs comprising more than 20 million nodes. Therefore, the proposed solution presents great potential for improving current electronic design automation environments.

Parallel computing is a trend to enhance scalability of electronic design automation (EDA) tools using widely available multicore platforms. In order to benefit from parallelism, well-known EDA algorithms have to be reformulated and optimized for multicore implementation. This paper introduces a set of principles to enable a fine-grain parallel AND-inverter graph (AIG) rewriting. It presents a novel method to discover and rewrite in parallel parts of the AIG, without the need for graph partitioning. Experiments show that, when synthesizing large designs composed of millions of AIG nodes, the parallel rewriting on 40 physical cores is up to 36x and 68x faster than ABC commands rewrite −l and drw, respectively, with comparable quality of results in terms of AIG size and depth.

Double-gate devices, like independent-gate (IG) FinFET, have introduced new possibilities and challenges in synthesis of transistor networks. Existing factorization methods and graph-based optimizations are not actually the most effective way to generate optimized IG FinFET based networks because only reducing the number of literals in a given Boolean expression does not guarantee the minimum transistor count. This paper presents two novel methods aiming the minimization of the number of devices in logic networks. The first contribution is a method for defactoring Boolean expressions able to apply the conventional factorization algorithms together with IG FinFET particularities, so improving it. The second contribution is a novel graph-based method that improves even more transistor arrangements by exploiting enhanced nonseries-parallel associations. Experimental results shown a significant reduction in the size of transistor networks delivered by the proposed methods.

Transistor network optimization represents an effective way of improving VLSI circuits. This paper proposes a novel method to automatically generate networks with minimal transistor count, starting from an irredundant sum-of-products expression as the input. The method is able to deliver both series-parallel (SP) and non-SP switch arrangements, improving speed, power dissipation, and area of CMOS gates. Experimental results demonstrate expected gains in comparison with related approaches.

The transistor arrangement optimization is an effective possibility to improve VLSI design, especially when generating CMOS logic gates to be inserted in standard cell libraries. This paper addresses this issue and presents a new methodology to generate efficient transistor networks. Starting from an input ISOP, the proposed method is capable to deliver series-parallel and non-series-parallel arrangements with reduced transistor count. By applying the proposed approach, it is possible to achieve optimized transistor arrangements since greedy choices are avoided during part of the generation process. The performed experiments have demonstrated the efficiency of this methodology when comparing to other available techniques.