1. A DMA and CACHE-based stress schema for burn-in of automotive microcontroller
    P. Bernardi, R. Cantoro, L. Gianotto, M. Restifo, E. Sanchez, F. Venini, D. Appello
    DOI: 10.1109/LATW.2017.7906767
    KEYWORDS: memory management; stress; random access memory; built-in self-test; automotive engineering; thermal stresses; performance evaluation
    ABSTRACT: Thermal and electrical stress phases are commonly applied to automotive devices at the end of manufacturing test to give rise to early life latent failures. This paper proposes a new methodology to optimize the stress procedures during the Burn-In phase. In the proposed method, stress of CPU, RAM memory and FLASH memory are run in parallel using DMA and CACHE interventions. The paper reports also some experimental results gathered in an automotive microcontroller, and a comparison between traditional and parallelized burn-in stress technique is also provided.

  2. Adaptive Batteries Exploiting On-Line Steady-State Evolution Strategy
    E. Fadda, G. Perboli, G. Squillero
    Applications of Evolutionary Computation
    DOI: 10.1007/978-3-319-55849-3_22
    KEYWORDS: optimisation; evolutionary strategy; battery; intelligent systems
    ABSTRACT: In energy distribution systems, uncertainty is the major single cause of power outages. In this paper, we consider the usage of electric batteries in order to mitigate it. We describe an intelligent battery able to maximize its own lifetime while guaranteeing to satisfy all the electric demand peaks. The battery exploits a customized steady-state evolution strategy to dynamically adapt its recharge strategy to changing environments. Experimental results on both synthetic and real data demonstrate the efficacy of the proposed solution.

  3. An Effective Fault-Injection Framework for Memory Reliability Enhancement Perspectives
    G. Harcha, P. Girard, A. Virazel
    Design &Technology of Integrated Systems in Nanoscale Era

  4. Multi-objective Evolutionary Algorithms for Influence Maximization in Social Networks
    D. Bucur, G. Iacca, A. Marcelli, G. Squillero, A. Tonda
    Applications of Evolutionary Computation
    DOI: 10.1007/978-3-319-55849-3_15
    KEYWORDS: social network; multi-objective evolutionary algorithms; influence maximization
    ABSTRACT: As the pervasiveness of social networks increases, new NP-hard related problems become interesting for the optimization community. The objective of influence maximization is to contact the largest possible number of nodes in a network, starting from a small set of seed nodes, and assuming a model for information propagation. This problem is of utmost practical importance for applications ranging from social studies to marketing. The influence maximization problem is typically formulated assuming that the number of the seed nodes is a parameter. Differently, in this paper, we choose to formulate it in a multi-objective fashion, considering the minimization of the number of seed nodes among the goals, and we tackle it with an evolutionary approach. As a result, we are able to identify sets of seed nodes of different size that spread influence the best, providing factual data to trade-off costs with quality of the result. The methodology is tested on two real-world case studies, using two different influence propagation models, and compared against state-of-the-art heuristic algorithms. The results show that the proposed approach is almost always able to outperform the heuristics.

  5. On the detection of board delay faults through the execution of functional programs
    G. An, R. Cantoro, E. Sanchez, M. Reorda
    DOI: 10.1109/LATW.2017.7906759
    KEYWORDS: computational modeling; ip networks; delays; circuit faults; integrated circuit modeling; random access memory; testing
    ABSTRACT: In the last years, the phenomenon of electronic products passing all tests by the manufacturer but failing in the field (No Fault Found, or NFF) attracted the attention of industries and researchers. Delay faults are supposed to be among the contributors to this phenomenon. Hence, companies are increasingly adopting functional test as a final step, which is expected to detect this kind of defects. This paper investigates the capabilities of detecting delay faults by several types of functional test, and proposes a method to write functional test programs able to detect most of the delay faults on the connections between the CPU and the memory.

  6. Radiation-induced SET on Flash-based FPGAs: Analysis and Filtering methods
    L. Sterpone, S. Azimi
    ARCS 2017 - 30th International Conference on Architecture of Computing Systems Workshop Proceedings
    KEYWORDS: redundancy; single event transients; flash-based fpgas; electrical injection; filtering
    ABSTRACT: Reliability of Integrated Circuits (ICs) it is nowadays a major concern for deep sub-micron technology. The progressive decreasing of device feature sizes provokes an increasing sensitiveness to radiation-induced particle strikes within the device silicon structure generating a larger number of Single Event Transients (SETs). In the present paper, we propose a new analysis to characterize the SET phenomena within Flashbased FPGAs. Besides, we developed a new mitigation strategy based on the modification of the place and routed design to improve the filtering capability selectively adding electrical resistive capacitive loads without introducing performance degradation and introducing a limited overhead in terms of routing segments. Experimental results performed on a various set of benchmark circuits shows a mitigation of SET improved of 3 orders of magnitude with respect to traditional logical filtering solutions with a minimal performance degradation of about 9%.