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Alberto Sangiovanni-Vincentelli

Researcher at University of California, Berkeley

Publications -  946
Citations -  47259

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.

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Journal ArticleDOI

Coping with latency in SOC design

TL;DR: Latency-insensitive design is the foundation of a correct-by-construction methodology for SOC design that can handle latency's increasing impact on deep-submicron technologies and facilitate the reuse of intellectual-property cores for building complex systems on chips.
Proceedings ArticleDOI

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

TL;DR: Li et al. as mentioned in this paper presented a framework to rapidly create point clouds with accurate point-level labels from a computer game, which can be used as training data for deep learning algorithms, while point clouds from user-configured scenes can also 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.
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Moving From Federated to Integrated Architectures in Automotive: The Role of Standards, Methods and Tools

TL;DR: In this paper, the authors provide a general overview of existing challenges and possible solutions to the design and analysis problem, with special focus on the automotive domain, with UML, AUTOSAR and synchronous reactive models, on which Simulink and SCADE are based.
Journal ArticleDOI

Scheduling for embedded real-time systems

TL;DR: The authors review several approaches to control-oriented and dataflow-oriented software scheduling to determine whether a given technique can satisfy deadlines, throughput, and other constraints for embedded real-time systems.
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Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control

TL;DR: A specification methodology and design space exploration framework are proposed to raise the level of abstraction at which building control systems are designed, to reduce design effort, and to lower implementation cost.