Author
Alberto Sangiovanni-Vincentelli
Other affiliations: National University of Singapore, Lawrence Berkeley National Laboratory, United Technologies ...read more
Bio: Alberto Sangiovanni-Vincentelli is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Logic synthesis & Finite-state machine. The author has an hindex of 99, co-authored 934 publications receiving 45201 citations. Previous affiliations of Alberto Sangiovanni-Vincentelli include National University of Singapore & Lawrence Berkeley National Laboratory.
Papers published on a yearly basis
Papers
More filters
••
10 Nov 1996TL;DR: It is found that it is possible to predict signal interaction by signal functionality alone, leading to a significant amount of robust switching isolation, independent of parasitics introduced by layout or semiconductor process.
Abstract: Maintaining signal integrity in digital systems is becoming increasingly difficult due to the rising number of analog effects seen in deep submicron design. One such effect, the signal crosstalk problem, is now a serious design concern. Signals which couple electrically may not affect system behavior because of timing or function in the digital domain. If we can isolate observable coupling effects then we can constrain layout synthesis to eliminate them. In this paper, we find that it is possible to predict signal interaction by signal functionality alone, leading to a significant amount of robust switching isolation, independent of parasitics introduced by layout or semiconductor process. We introduce techniques to predict signal interaction using functional sensitivity analysis. In general sequential networks we find that significant switching isolation can be extracted with efficient sensitivity analysis algorithms, thus giving promise to the goal of synthesizing layout free from crosstalk effects.
53 citations
••
07 Aug 2018
TL;DR: A new satisfiability modulo convex programming (SMC) framework that integrates SAT solving and convex optimization to efficiently reason about Boolean and conveX constraints at the same time, and can handle more complex problem instances than state-of-the-art alternative techniques based on SMT solving and mixed integer convex Programming.
Abstract: The design of cyber–physical systems (CPSs) requires methods and tools that can efficiently reason about the interaction between discrete models, e.g., representing the behaviors of “cyber” components, and continuous models of physical processes. Boolean methods such as satisfiability (SAT) solving are successful in tackling large combinatorial search problems for the design and verification of hardware and software components. On the other hand, problems in control, communications, signal processing, and machine learning often rely on convex programming as a powerful solution engine. However, despite their strengths, neither approach would work in isolation for CPSs. In this paper, we present a new satisfiability modulo convex programming (SMC) framework that integrates SAT solving and convex optimization to efficiently reason about Boolean and convex constraints at the same time. We exploit the properties of a class of logic formulas over Boolean and nonlinear real predicates, termed monotone satisfiability modulo convex formulas, whose satisfiability can be checked via a finite number of convex programs. Following the lazy satisfiability modulo theory (SMT) paradigm, we develop a new decision procedure for monotone SMC formulas, which coordinates SAT solving and convex programming to provide a satisfying assignment or determine that the formula is unsatisfiable. A key step in our coordination scheme is the efficient generation of succinct infeasibility proofs for inconsistent constraints that can support conflict-driven learning and accelerate the search. We demonstrate our approach on different CPS design problems, including spacecraft docking mission control, robotic motion planning, and secure state estimation. We show that SMC can handle more complex problem instances than state-of-the-art alternative techniques based on SMT solving and mixed integer convex programming.
53 citations
••
TL;DR: These results demonstrate that the statistical inference can be used for predicting the distribution of the response time of a CAN message, once its priority has been assigned, from limited information such as the bus utilization of higher priority messages.
Abstract: Automotive electrical/electronic (E/E) architectures need to be evaluated and selected based on the estimated performance of the functions deployed on them before the details of these functions are known. End-to-end delays of controls must be estimated using incomplete and aggregate information on the computation and communication load for ECUs and buses. We describe the use of statistical analysis to compute the probability distribution of Controller Area Network (CAN) message response times when only partial information is available about the functionality and architecture of a vehicle. We provide results compared to simulations as well as trace data. These results demonstrate that our statistical inference can be used for predicting the distribution of the response time of a CAN message, once its priority has been assigned, from limited information such as the bus utilization of higher priority messages.
52 citations
••
13 Apr 2017
TL;DR: This paper addresses the problem of determining the satisfiability of a Boolean combination of convex constraints over the real numbers, which is common in the context of hybrid system verification and control, and proposes a suite of algorithms that can trade complexity with the minimality of the generated infeasibility certificates.
Abstract: We address the problem of determining the satisfiability of a Boolean combination of convex constraints over the real numbers, which is common in the context of hybrid system verification and control. We first show that a special type of logic formulas, termed monotone Satisfiability Modulo Convex (SMC) formulas, is the most general class of formulas over Boolean and nonlinear real predicates that reduce to convex programs for any satisfying assignment of the Boolean variables. For this class of formulas, we develop a new satisfiability modulo convex optimization procedure that uses a lazy combination of SAT solving and convex programming to provide a satisfying assignment or determine that the formula is unsatisfiable. Our approach can then leverage the efficiency and the formal guarantees of state-of-the-art algorithms in both the Boolean and convex analysis domains. A key step in lazy satisfiability solving is the generation of succinct infeasibility proofs that can support conflict-driven learning and decrease the number of iterations between the SAT and the theory solver. For this purpose, we propose a suite of algorithms that can trade complexity with the minimality of the generated infeasibility certificates. Remarkably, we show that a minimal infeasibility certificate can be generated by simply solving one convex program for a sub-class of SMC formulas, namely ordered positive unate SMC formulas, that have additional monotonicity properties. Perhaps surprisingly, ordered positive unate formulas appear themselves very frequently in a variety of practical applications. By exploiting the properties of monotone SMC formulas, we can then build and demonstrate effective and scalable decision procedures for problems in hybrid system verification and control, including secure state estimation and robotic motion planning.
52 citations
01 Jul 2015
TL;DR: This paper intends to provide treatment where contracts are precisely defined and characterized so that they can be used in design methodologies such as the ones mentioned above with no ambiguity, and provides an important link between interface and contract theories to show similarities and correspondences.
Abstract: Aircrafts, trains, cars, plants, distributed telecommunication military or health care systems,
and more, involve systems design as a critical step. Complexity has caused system design times and costs
to go severely over budget so as to threaten the health of entire industrial sectors. Heuristic methods and
standard practices do not seem to scale with complexity so that novel design methods and tools based on a
strong theoretical foundation are sorely needed. Model-based design as well as other methodologies such
as layered and compositional design have been used recently but a unified intellectual framework with a
complete design flow supported by formal tools is still lacking.
Recently an “orthogonal” approach has been proposed that can be applied to all methodologies introduced
thus far to provide a rigorous scaffolding for verification, analysis and abstraction/refinement: contractbased
design. Several results have been obtained in this domain but a unified treatment of the topic that can
help in putting contract-based design in perspective is missing. This paper intends to provide such treatment
where contracts are precisely defined and characterized so that they can be used in design methodologies
such as the ones mentioned above with no ambiguity. In addition, the paper provides an important link
between interface and contract theories to show similarities and correspondences.
This paper is complemented by a companion paper where contract based design is illustrated through
use cases.
52 citations
Cited by
More filters
••
01 Jan 1998TL;DR: In this article, a graph transformer network (GTN) is proposed for handwritten character recognition, which can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters.
Abstract: Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten character recognition and compares them on a standard handwritten digit recognition task. Convolutional neural networks, which are specifically designed to deal with the variability of 2D shapes, are shown to outperform all other techniques. Real-life document recognition systems are composed of multiple modules including field extraction, segmentation recognition, and language modeling. A new learning paradigm, called graph transformer networks (GTN), allows such multimodule systems to be trained globally using gradient-based methods so as to minimize an overall performance measure. Two systems for online handwriting recognition are described. Experiments demonstrate the advantage of global training, and the flexibility of graph transformer networks. A graph transformer network for reading a bank cheque is also described. It uses convolutional neural network character recognizers combined with global training techniques to provide record accuracy on business and personal cheques. It is deployed commercially and reads several million cheques per day.
42,067 citations
••
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Abstract: A new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented. By means of an extensive testbed it is demonstrated that the new method converges faster and with more certainty than many other acclaimed global optimization methods. The new method requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
24,053 citations
••
[...]
TL;DR: In this paper, a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) is presented.
Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These
9,929 citations
••
TL;DR: In this paper, the authors present a data structure for representing Boolean functions and an associated set of manipulation algorithms, which have time complexity proportional to the sizes of the graphs being operated on, and hence are quite efficient as long as the graphs do not grow too large.
Abstract: In this paper we present a new data structure for representing Boolean functions and an associated set of manipulation algorithms. Functions are represented by directed, acyclic graphs in a manner similar to the representations introduced by Lee [1] and Akers [2], but with further restrictions on the ordering of decision variables in the graph. Although a function requires, in the worst case, a graph of size exponential in the number of arguments, many of the functions encountered in typical applications have a more reasonable representation. Our algorithms have time complexity proportional to the sizes of the graphs being operated on, and hence are quite efficient as long as the graphs do not grow too large. We present experimental results from applying these algorithms to problems in logic design verification that demonstrate the practicality of our approach.
9,021 citations
•
25 Apr 2008
TL;DR: Principles of Model Checking offers a comprehensive introduction to model checking that is not only a text suitable for classroom use but also a valuable reference for researchers and practitioners in the field.
Abstract: Our growing dependence on increasingly complex computer and software systems necessitates the development of formalisms, techniques, and tools for assessing functional properties of these systems. One such technique that has emerged in the last twenty years is model checking, which systematically (and automatically) checks whether a model of a given system satisfies a desired property such as deadlock freedom, invariants, and request-response properties. This automated technique for verification and debugging has developed into a mature and widely used approach with many applications. Principles of Model Checking offers a comprehensive introduction to model checking that is not only a text suitable for classroom use but also a valuable reference for researchers and practitioners in the field. The book begins with the basic principles for modeling concurrent and communicating systems, introduces different classes of properties (including safety and liveness), presents the notion of fairness, and provides automata-based algorithms for these properties. It introduces the temporal logics LTL and CTL, compares them, and covers algorithms for verifying these logics, discussing real-time systems as well as systems subject to random phenomena. Separate chapters treat such efficiency-improving techniques as abstraction and symbolic manipulation. The book includes an extensive set of examples (most of which run through several chapters) and a complete set of basic results accompanied by detailed proofs. Each chapter concludes with a summary, bibliographic notes, and an extensive list of exercises of both practical and theoretical nature.
4,905 citations