Formal Methods in Computer-aided Design

The VLSI CAD flow encompasses an abundance of critical NP-complete and PSPACE-complete problems. Instead of developing a dedicated algorithm for each, the trend during the last decade has been to encode them in formal languages, such as Boolean satisfiability (SAT) and quantified Boolean formulas (QBFs), and focus academic resources on improving SAT and QBF solvers. The significant progress of these solvers has validated this strategy. This dissertation contributes to the further advancement of formal techniques in CAD. Today, the verification and debugging of increasingly complex RTL designs can consume up to 70% of the VLSI design cycle. In particular, RTL debug is a manual, resource-intensive task in the industry. The first contribution of this thesis is an in-depth examination of the factors affecting the theoretical computational complexity of debugging. It is established that most variations of the debugging problem are NP-complete. Automated debugging tools return all potential error sources in the RTL, called solutions, that can explain a given failing error trace. Finding each solution requires a separate call to a formal engine, which is computationally expensive. The second contribution of this dissertation comprises techniques for reducing the number of such iterations, by leveraging dominance relationships between RTL blocks to imply solutions. Extensive experiments on industrial designs show a three-fold reduction in the number of formal engine calls due to solution implications, resulting in a 1.64x overall speed-up. The third contribution aims to advance the state-of-the-art of QBF solvers, whose progress has not been as impressive as that of SAT solvers. We present a framework for using complete dominators to preprocess and reduce QBFs with an inherent circuit structure, which is common in encodings of PSPACE-complete CAD problems. Experiments show that three modern QBF solvers together solve 55% of preprocessed QBF instances, compared to none without preprocessing. The final contribution consists of a series of QBF encodings for evaluating the reconfigurability of partially programmable circuits (PPCs). The metrics of fault tolerance, design error tolerance and engineering change coverage are defined for PPCs and encoded using QBFs. These formulations along with experimental results demonstrate the theoretical and practical appropriateness of QBFs for dealing with reconfigurability.Ph

On Statistical Timing Analysis with Inter- and Intra-die Variations

In this paper, we highlight a fast, effective and practical statistical approach that deals with inter and intra-die variations in VLSI chips. Our methodology is applied to a number of random variables while accounting for spatial correlations. Our methodology sorts the Probability Density Functions (PDFs) of the critical paths of a circuit based on a confidence-point. We show the mathematical accuracy of our method as well as implement a typical program to test it on various benchmarks. We find that worst-case analysis overestimates path delays by more than 50 % and that a path’s probabilistic rank with respect to delay is very different from its deterministic rank.

A Performance-Driven QBF-Based Iterative Logic Array Representation with Applications to Verification, Debug and Test

Abstract — Many CAD for VLSI techniques use time-frame expansion, also known as the Iterative Logic Array representation, to model the sequential behavior of a system. Replicating industrialsize designs for many time-frames may impose impractically excessive memory requirements. This work proposes a performancedriven, succinct and parametrizable Quantified Boolean Formula (QBF) satisfiability encoding and its hardware implementation for modeling sequential circuit behavior. This encoding is then applied to three notable CAD problems, namely Bounded Model Checking (BMC), sequential test generation and design debugging. Extensive experiments on industrial circuits confirm outstanding run-time and memory gains compared to state-of-the-art techniques, promoting the use of QBF in CAD for VLSI. I

Non-Solution Implications using Reverse Domination in a Modern SAT-based Debugging Environment

Abstract—With the growing complexity of VLSI designs, functional debugging has become a bottleneck in modern CAD flows. To alleviate this cost, various SAT-based techniques have been developed to automate bug localization in the RTL. In this context, dominance relationships between circuit blocks have been recently shown to reduce the number of SAT solver calls, using the concept of solution implications. This paper first introduces the dual concepts of reverse domination and non-solution implications. A SAT solver is tailored to leverage reverse dominators for the early on-the-fly detection of bug-free components. These are nonsolution areas and their early pruning significantly reduces the the debugging search-space. This process is expedited by branching on error-select variables first. Extensive experiments on tough real-life industrial debugging cases show an average speedup of 1.7x in SAT solving time over the state-of-the-art, a testimony of the practicality and effectiveness of the proposed approach. I

Fault diagnosis using quantified boolean formulas

Abstract — Automatic debugging of sequential circuits has been considered a practically intractable task due to the excessive memory and run-time requirements associated with tackling industrial-size problems. This paper proposes a novel Quantified Boolean Formula (QBF) based approach for fault diagnosis in sequential circuits. A performance-driven succinct QBF encoding of the problem, coupled with the tremendous present-day advances in QBF solvers make this strategy a successful one. Extensive experiments on industrial circuits confirm the memory advantage and demonstrate the outstanding performance of the proposed framework. I