Alan Mishchenko

ABC: an academic industrial-strength verification tool

ABC is a public-domain system for logic synthesis and formal verification of binary logic circuits appearing in synchronous hardware designs ABC combines scalable logic transformations based on And-Inverter Graphs (AIGs), with a variety of innovative algorithms A focus on the synergy of sequential synthesis and sequential verification leads to improvements in both domains This paper introduces ABC, motivates its development, and illustrates its use in formal verification.

DAG-aware AIG rewriting a fresh look at combinational logic synthesis

This paper presents a technique for preprocessing combinational logic before technology mapping. The technique is based on the representation of combinational logic using and-inverter graphs (AIGs), a networks of two-input ANDs and inverters. The optimization works by alternating DAG-aware AIG rewriting, which reduces area by sharing common logic without increasing delay, and algebraic AIG balancing, which minimizes delay without increasing area. The new technology-independent flow is implemented in a public-domain tool ABC. Experiments on large industrial benchmarks show that the proposed methodology scales to very large designs and is several orders of magnitude faster than SIS and MVSIS while offering comparable or better quality when measured by the quality of the network after mapping

Improvements to combinational equivalence checking

The paper explores several ways to improve the speed and capacity of combinational equivalence checking based on Boolean satisfiability (SAT). State-of-the-art methods use simulation and BDD/SAT sweeping on the input side (i.e. proving equivalence of some internal nodes in a topological order), interleaved with attempts to run SAT on the output (i.e. proving equivalence of the output to constant 0). This paper improves on this method by (a) using more intelligent simulation, (b) using CNF-based SAT with circuit-based decision heuristics, and (c) interleaving SAT with low-effort logic synthesis. Experimental results on public and industrial benchmarks demonstrate substantial reductions in runtime, compared to the current methods. In several cases, the new solver succeeded in solving previously unsolved problems

Combinational and sequential mapping with priority cuts

An algorithm for technology mapping of combinational and sequential logic networks is proposed and applied to mapping into K-input lookup-tables (K-LUTs). The new algorithm avoids the hurdle of computing all K-input cuts while preserving the quality of the results, in terms of area and depth. The memory and runtime of the proposed algorithm are linear in circuit size and quite affordable even for large industrial designs. For example, computing a good quality 6-LUT mapping of an AIG with 1 M nodes takes 150 Mb of RAM and 1 minute on a typical laptop. An extension of the algorithm allows for sequential mapping, which searches the combined space of all possible mappings and retimings. This leads to an 18-22% improvement in depth with a 3-5% LOT count penalty, compared to combinational mapping followed by retiming.

Improvements to Technology Mapping for LUT-Based FPGAs

This paper presents several orthogonal improvements to the state-of-the-art lookup table (LUT)-based field-programmable gate array (FPGA) technology mapping. The improvements target the delay and area of technology mapping as well as the runtime and memory requirements. 1) Improved cut enumeration computes all K-feasible cuts, without pruning, for up to seven inputs for the largest Microelectronics Center of North Carolina benchmarks. A new technique for on-the-fly cut dropping reduces, by orders of magnitude, the memory needed to represent cuts for large designs. 2) The notion of cut factorization is introduced, in which one computes a subset of cuts for a node and generates other cuts from that subset as needed. Two cut factorization schemes are presented, and a new algorithm that uses cut factorization for delay-oriented mapping for FPGAs with large LUTs is proposed. 3) Improved area recovery leads to mappings with the area, on average, 6% smaller than the previous best work while preserving the delay optimality when starting from the same optimized netlists. 4) Lossless synthesis accumulates alternative circuit structures seen during logic optimization. Extending the mapper to use structural choices reduces the delay, on average, by 6% and the area by 12%, compared with the previous work, while increasing the runtime 1.6 times. Performing five iterations of mapping with choices reduces the delay by 10% and the area by 19% while increasing the runtime eight times. These improvements, on top of the state-of-the-art methods for LUT mapping, are available in the package ABC

Reducing structural bias in technology mapping

Technology mapping, based on directed acyclic graph covering, suffers from the problem of structural bias: The structure of the mapped netlist depends strongly on the subject graph. In this paper, the authors present a new mapper aimed at mitigating structural bias. It is based on a simplified cut-based Boolean-matching algorithm, and using the speed afforded by this simplification, they explore two ideas to reduce structural bias. The first, called lossless synthesis, leverages recent advances in structure-based combinational-equivalence checking to combine the different networks seen during technology-independent synthesis into a single network with choices in a scalable manner. They show how cut-based mapping extends naturally to handle such networks with choices. The second idea is to combine several library gates into a single gate (called a supergate) in order to make the matching process less local. They show how supergates help address the structural-bias problem and how they fit naturally into the cut-based Boolean-matching scheme. An implementation based on these ideas significantly outperforms state-of-the-art mappers in terms of delay, area, and run-time on academic and industrial benchmarks

Applying logic synthesis for speeding up SAT

SAT solvers are often challenged with very hard problems that remain unsolved after hours of CPU time. The research community meets the challenge in two ways: (1) by improving the SAT solver technology, for example, perfecting heuristics for variable ordering, and (2) by inventing new ways of constructing simpler SAT problems, either using domain specific information during the translation from the original problem to CNF, or by applying a more universal CNF simplification procedure after the translation. This paper explores preprocessing of circuit-based SAT problems using recent advances in logic synthesis. Two fast logic synthesis techniques are considered: DAG-aware logic minimization and a novel type of structural technology mapping, which reduces the size of the CNF derived from the circuit. These techniques are experimentally compared to CNF-based preprocessing. The conclusion is that the proposed techniques are complementary to CNF-based preprocessing and speedup SAT solving substantially on industrial examples.

Improvements to technology mapping for LUT-based FPGAs

This paper presents several orthogonal improvements to the state-of-the-art lookup table (LUT)-based field-programmable gate array (FPGA) technology mapping. The improvements target the delay and area of technology mapping as well as the runtime and memory requirements. 1) Improved cut enumeration computes all K-feasible cuts, without pruning, for up to seven inputs for the largest Microelectronics Center of North Carolina benchmarks. A new technique for on-the-fly cut dropping reduces, by orders of magnitude, the memory needed to represent cuts for large designs. 2) The notion of cut factorization is introduced, in which one computes a subset of cuts for a node and generates other cuts from that subset as needed. Two cut factorization schemes are presented, and a new algorithm that uses cut factorization for delay-oriented mapping for FPGAs with large LUTs is proposed. 3) Improved area recovery leads to mappings with the area, on average, 6% smaller than the previous best work while preserving the delay optimality when starting from the same optimized netlists. 4) Lossless synthesis accumulates alternative circuit structures seen during logic optimization. Extending the mapper to use structural choices reduces the delay, on average, by 6% and the area by 12%, compared with the previous work, while increasing the runtime 1.6 times. Performing five iterations of mapping with choices reduces the delay by 10% and the area by 19% while increasing the runtime eight times. These improvements, on top of the state-of-the-art methods for LUT mapping, are available in the package ABC

Scalable exploration of functional dependency by interpolation and incremental SAT solving

Functional dependency is concerned with rewriting a Boolean function f as a function h over a set of base functions {g1, ..., gn), i.e. f = h(g1, ..., gn). It plays an important role in many aspects of electronic design automation (EDA), ranging from logic synthesis to formal verification. Prior approaches to the exploration of functional dependency are based on binary decision diagrams (BDDs), which may not be easily scalable to large designs. This paper proposes a novel reformulation that extensively exploits the capability of modern satisfiability (SAT) solvers. Thereby, functional dependency is detected effectively through incremental SAT solving, and the dependency function h, if it exists, is obtained through Craig interpolation. The main strengths of the proposed approach include: (1) fast detection of functional dependency with modest memory consumption and thus scalable to large designs, (2) a full capacity to handle a large set of base functions and thus discovering dependency whenever exists, and (3) potential application to large-scale logic optimization and verification reduction. Experimental results show the proposed method is far superior to prior work and scales well in dealing with the largest ISCAS89 and ITC99 benchmark circuits with up to 200 K gates.

A new-enhanced constructive decomposition and mapping algorithm

Structuring and mapping of the Boolean function is an important problem in the design of complex integrated circuits. Library-aware constructive decomposition offers a solution to this problem. This paper proposes novel techniques to improve the quality and runtime of constructive decomposition. The improvements are effective both in the stand-alone mapping procedure and in the context of re-synthesis applied to a mapped multi-level network. Experiments with public and proprietary benchmarks show promising results.