Alberto Sangiovanni-Vincentelli

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.

An industrial system engineering process integrating model driven architecture and model based design

Abstract: We present an industrial model-driven engineering process for the design and development of complex distributed embedded systems. We outline the main steps in the process and the evaluation of its use in the context of a radar application. We show the methods and tools that have been developed to allow interoperability among requirements management, SysML modeling and MBD simulation and code generation.

Theory and algorithms for face hypercube embedding

Abstract: We present a new matrix formulation of the face hypercube embedding problem that motivates the design of an efficient search strategy to find an encoding that satisfies all faces of minimum length. Increasing dimensions of the Boolean space are explored; for a given dimension constraints are satisfied one at a time. The following features help to reduce the nodes of the solution space that must be explored: candidate cubes instead of candidate codes are generated, cubes yielding symmetric solutions are not generated, a smaller sufficient set of solutions (producing basic sections) is explored, necessary conditions help discard unsuitable candidate cubes, early detection that a partial solution cannot be extended to be a global solution prunes infeasible portions of the search tree. We have implemented a prototype package minimum input satisfaction kernel (MINSK) based on the previous ideas and run experiments to evaluate it. The experiments show that MINSK is faster and solves more problems than any available algorithm. Moreover, MINSK is a robust algorithm, while most of the proposed alternatives are not. Besides most problems of the complete Microelectronics Center of North Carolina (MCNC) benchmark suite, other solved examples include an important set of decoder programmable logic arrays (PLA's) coming from the design of microprocessor instruction sets.

Robust strategy synthesis for probabilistic systems applied to risk-limiting renewable-energy pricing

Abstract: We address the problem of synthesizing control strategies for Ellipsoidal Markov Decision Processes (EMDP), i.e., MDPs whose transition probabilities are expressed using ellipsoidal uncertainty sets. The synthesized strategy aims to maximize the total expected reward of the EMDP, constrained to a specification expressed in Probabilistic Computation Tree Logic (PCTL). We prove that the EMDP strategy synthesis problem for the fragment of PCTL disabling operators with a finite time bound is NP-complete and propose a novel sound and complete algorithm to solve it. We apply these results to the problem of synthesizing optimal energy pricing and dispatch strategies in smart grids that integrate renewable sources of energy. We use rewards to maximize the profit of the network operator and a PCTL specification to constrain the risk of power unbalance and guarantee quality-of-service for the users. The EMDP model used to represent the decision-making scenario was trained with measured data and quantitatively captures the uncertainty in the prediction of energy generation. An experimental comparison shows the effectiveness of our method with respect to previous approaches presented in the literature.

Some Considerations on Field-Programmable Gate Arrays and Their Impact on System Design

Abstract: User programmable devices are becoming more and more important for system design because of their flexibility that allows much shorter design time and hence better time-to-market. The use of programmable devices spans rapid prototyping and dynamically reconfigurable systems. The market is projected to raise rapidly to levels that make this type of devices very appealing for merchant IC manufacturers. Some of the issues related to the future of these devices as well as to the future of system design methodologies are presented.

Hybrid tracking control for spark-ignition engines

Abstract: The design of a torque tracking controller for a spark ignition engine is presented. A hybrid model that describes the interacting behavior of the intake manifold, the engine, the power-train and the catalytic converter is illustrated. The proposed control is obtained by: 1) decoupling the control problem into two sub-problems; and 2) relaxing each of the two subproblems to yield problems that can be solved with classical control techniques. The control law so obtained is mapped back into the hybrid domain. The quality of the proposed hybrid control feedback is demonstrated analytically and by simulations on the full-fledged hybrid model.

Gradient-based learning applied to document recognition

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.

Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces

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.

Phd by thesis

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

Graph-Based Algorithms for Boolean Function Manipulation

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.

Principles of Model Checking

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.