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.

Solving the state assignment problem for signal transition graphs

Abstract: The authors propose a novel framework to solve the state assignment problem arising from the signal transition graph (STG) representation of an asynchronous circuit They first solve the STG state assignment problem by minimizing the number of states in the corresponding finite-state machine (FSM) and by using a critical race-free state assignment technique State signal transitions may be added to the original STG A lower bound on the number of signals necessary to implement the STG is given The technique significantly increases the applicability of STGs for specifying asynchronous circuits >

High performance BDD package by exploiting memory hierarchy

Abstract: The success of binary decision diagram (BDD) based algorithms for verification depend on the availability of a high performance package to manipulate very large BDDs. State-of-the-art BDD packages, based on the conventional depth-first technique, limit the size of the BDDs due to a disorderly memory access patterns that results in unacceptably high elapsed time when the BDD size exceeds the main memory capacity. We present a high performance BDD package that enables manipulation of very large BDDs by using an iterative breadth-first technique directed towards localizing the memory accesses to exploit the memory system hierarchy. The new memory-oriented performance features of this package are: 1) an architecture independent customized memory management scheme, 2) the ability to issue multiple independent BDD operations (superscalarity), and 3) the ability to perform multiple BDD operations even when the operands of some BDD operations are the result of some other operations yet to be completed (pipelining). A comprehensive set of BDD manipulation algorithms are implemented using the above techniques. Unlike the breadth-first algorithms presented in the literature, the new package is faster than the state-of-the-art BDD package by a factor of up to 15, even for the BDD sizes that fit within the main memory. For BDD sizes that do not fit within the main memory, a performance improvement of up to a factor of 100 can be achieved.

A Service-Based Universal Application Interface for Ad-hoc Wireless Sensor Networks

Abstract: This paper addresses the fundamental issue of defining a standard set of services and interface primitives which should be made available to an application programmer independently on their implementation on any present and future sensor network platform. As the definition of sockets has made the use of communication services in the Internet independent of the underlying protocol stack, communication medium and even operating system, the application interface we propose identifies an abstraction that is offered to any sensor network application and supported by any sensor network platform. The distributed service platform we introduce builds on the query/command paradigm already used in several sensor network implementations and includes time synchronization, location and naming services that support the communication and coordination among application components.

metroII: A design environment for cyber-physical systems

Abstract: Cyber-Physical Systems are integrations of computation and physical processes and as such, will be increasingly relevant to industry and people. The complexity of designing CPS resides in their heterogeneity. Heterogeneity manifest itself in modeling their functionality as well as in the implementation platforms that include a multiplicity of components such as microprocessors, signal processors, peripherals, memories, sensors and actuators often integrated on a single chip or on a small package such as a multi-chip module. We need a methodology, tools and environments where heterogeneity can be dealt with at all levels of abstraction and where different tools can be integrated. We present here Platform-Based Design as the CPS methodology of choice and metroII, a design environment that supports it. We present the metamodeling approach followed in metroII, how to couple the functionality and implementation platforms of CPS, and the simulation technology that supports the analysis of CPS and of their implementation. We also present examples of use and the integration of metroII with another popular design environment developed at Verimag, BIP.

A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving

Abstract: 3D LiDAR scanners are playing an increasingly important role in autonomous driving as they can generate depth information of the environment. However, creating large 3D LiDAR point cloud datasets with point-level labels requires a significant amount of manual annotation. This jeopardizes the efficient development of supervised deep learning algorithms which are often data-hungry. We present a framework to rapidly create point clouds with accurate point-level labels from a computer game. The framework supports data collection from both auto-driving scenes and user-configured scenes. Point clouds from auto-driving scenes can be used as training data for deep learning algorithms, while point clouds from user-configured scenes can be used to systematically test the vulnerability of a neural network, and use the falsifying examples to make the neural network more robust through retraining. In addition, the scene images can be captured simultaneously in order for sensor fusion tasks, with a method proposed to do automatic calibration between the point clouds and captured scene images. We show a significant improvement in accuracy (+9%) in point cloud segmentation by augmenting the training dataset with the generated synthesized data. Our experiments also show by testing and retraining the network using point clouds from user-configured scenes, the weakness/blind spots of the neural network can be fixed.

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.