Matteo Sonza Reorda

Bio: Matteo Sonza Reorda is an academic researcher from Polytechnic University of Turin. The author has contributed to research in topics: Fault coverage & Automatic test pattern generation. The author has an hindex of 32, co-authored 295 publications receiving 4525 citations. Previous affiliations of Matteo Sonza Reorda include University of California, Riverside & NXP Semiconductors.

In-field test of safety-critical systems: is functional test a feasible solution?

Abstract: The growing usage of electronic systems in safety- and mission-critical applications, together with the increased susceptibility of electronic devices to faults arising during the operational phase mandate for the availability of effective solutions able to face the effects of these faults. When the target system includes a processor, one possible solution is based on running suitable test programs able to detect the occurrence of faults. This solution provides several advantages (e.g., in terms of flexibility, IP protection, and defect coverage), although it is limited by the cost for developing the test programs. This paper overviews the state of the art in the area, and discusses the trends in the area.

VLSI-SoC: Opportunities and Challenges Beyond the Internet of Things

Abstract: Level shifters to convert signal swings from low-voltage (VDDL) to high-voltage (VDDH) are required at the boundary of voltage domains in SoC employing multiple supply voltages. However, they cost delay, power and area in addition to increasing the complexity of physical design. This paper proposes a level-shifter-less (LSL) approach to use a reverse body bias (RBB) at pMOS transistors in the VDDH domain and superior threshold-voltage modulation capability of FD-SOI devices. Simulation results and measurements of a fabricated chip showed that the chip applying the LSL approach correctly operates at VDDL = 0.6 V and VDDH = 1.2 V under 2 V pMOS RBB while suppressing the static dc current in the VDDH domain. We also demonstrate that adaptive RBB control for pMOS can maintain effectiveness of this approach under process and temperature variations.

La formazione a distanza al Politecnico di Torino: nuovi modelli e strumenti

Abstract: Il Politecnico di Torino è attivo nel campo della formazione a distanza da oltre 10 anni, nel quale ha sempre giocato un ruolo di innovazione e sperimentazione per quanto riguarda sia le tecnologie, sia le metodologie didattiche ed organizzative. Dall’anno accademico 2010/2011, utilizzando una serie di sperimentazioni precedenti, e contestualmente all’adozione di un nuovo modello didattico compatibile con i requisiti del DM270, il Politecnico di Torino ha ripensato la propria offerta in termini di servizi didattici online e corsi di laurea fruibili a distanza. Questo articolo illustra il modello utilizzato, che si basa sulla sinergia tra il servizio di registrazione e streaming delle lezioni in aula, la disponibilità di tutori on-line e di una specifica piattaforma didattica per studenti non frequentanti, e l’esistenza di sedi decentrate sul territorio. L’articolo illustra altresì i primi risultati ottenuti, dal punto di vista qualitativo e qualitativo, dopo il primo semestre di funzionamento del modello.

Modular Functional Testing: Targeting the Small Embedded Memories in GPUs.

Abstract: Graphic Processing Units (GPUs) are promising solutions in safety-critical applications, e.g., in the automotive domain. In these applications, reliability and functional safety are relevant factors. Nowadays, many challenges are impacting the implementation of high-performance devices, including GPUs. Moreover, there is the need for effective fault detection solutions to guarantee the correct in-field operation. This work describes a modular approach to develop functional testing solutions based on the non-invasive Software-Based Self-Test (SBST) strategy. We propose a scalar and modular mechanism to develop test programs based on schematic organizations of functions allowing the exploration of different solutions using software functions. The FlexGripPlus model was employed to evaluate experimentally the proposed strategies, targeting the embedded memories in the GPU. Results show that the proposed strategies are effective to test the target structures and detect from 98% up to 100% of permanent stuck-at faults.

Multiobjective evolutionary algorithms: classifications, analyses, and new innovations

Abstract: : This research organizes, presents, and analyzes contemporary Multiobjective Evolutionary Algorithm (MOEA) research and associated Multiobjective Optimization Problems (MOPs). Using a consistent MOEA terminology and notation, each cited MOEAs' key factors are presented in tabular form for ease of MOEA identification and selection. A detailed quantitative and qualitative MOEA analysis is presented, providing a basis for conclusions about various MOEA-related issues. The traditional notion of building blocks is extended to the MOP domain in an effort to develop more effective and efficient MOEAs. Additionally, the MOEA community's limited test suites contain various functions whose origins and rationale for use are often unknown. Thus, using general test suite guidelines appropriate MOEA test function suites are substantiated and generated. An experimental methodology incorporating a solution database and appropriate metrics is offered as a proposed evaluation framework allowing absolute comparisons of specific MOEA approaches. Taken together, this document's classifications, analyses, and new innovations present a complete, contemporary view of current MOEA "state of the art" and possible future research. Researchers with basic EA knowledge may also use part of it as a largely self-contained introduction to MOEAs.

Algorithms for VLSI Physical Design Automation

Abstract: From the Publisher: This work covers all aspects of physical design. The book is a core reference for graduate students and CAD professionals. For students, concept and algorithms are presented in an intuitive manner. For CAD professionals, the material presents a balance of theory and practice. An extensive bibliography is provided which is useful for finding advanced material on a topic. At the end of each chapter, exercises are provided, which range in complexity from simple to research level.

Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators

Abstract: This paper is the result of a literature study carried out by the authors. It is a review of the different attempts made to solve the Travelling Salesman Problem with Genetic Algorithms. We present crossover and mutation operators, developed to tackle the Travelling Salesman Problem with Genetic Algorithms with different representations such as: binary representation, path representation, adjacency representation, ordinal representation and matrix representation. Likewise, we show the experimental results obtained with different standard examples using combination of crossover and mutation operators in relation with path representation.

A Taxonomy of Hybrid Metaheuristics

Abstract: Hybrid metaheuristics have received considerable interest these recent years in the field of combinatorial optimization. A wide variety of hybrid approaches have been proposed in the literature. In this paper, a taxonomy of hybrid metaheuristics is presented in an attempt to provide a common terminology and classification mechanisms. The taxonomy, while presented in terms of metaheuristics, is also applicable to most types of heuristics and exact optimization algorithms. As an illustration of the usefulness of the taxonomy an annoted bibliography is given which classifies a large number of hybrid approaches according to the taxonomy.

Interpolation and SAT-based model checking

Abstract: We consider a fully SAT-based method of unbounded symbolic model checking based on computing Craig interpolants. In benchmark studies using a set of large industrial circuit verification instances, this method is greatly more efficient than BDD-based symbolic model checking, and compares favorably to some recent SAT-based model checking methods on positive instances.