Grenoble, France


Grenoble, France
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Cheminet A.,ONERA | Hubert G.,ONERA | Lacoste V.,Institute for Radiological Protection and Nuclear Safety | Velazco R.,TIMA Labs | Boscher D.,ONERA
IEEE Transactions on Nuclear Science | Year: 2013

A new platform dedicated to the long-term characterization of the Atmospheric Natural Radiative Environment at mountain altitude (Pic du Midi, +2885 m) is presented. The performance of a high energy neutron spectrometer is established with measurements performed in a realistic neutron field and by comparison with the neutron monitors. A SEE-rate prediction approach is also used on a 90 nm SRAM memory array which was irradiated at CERF and set up at the Pic du Midi during almost one year. © 2013 IEEE.

Mansour W.,TIMA Labs | Marques-Costa G.,TIMA Labs | Velazco R.,TIMA Labs
2013 25th International Conference on Microelectronics, ICM 2013 | Year: 2013

Self-convergence is a property that allows distributed systems, when perturbed or badly initialized, to recover a correct operation within finite number of calculation steps. In this paper, an FPGA implementation of this algorithm is presented. The intrinsic robustness of the studied implementation with respect to soft errors resulting from radiation effects is explored by means of a fault-injected method. Obtained results put in evidence the fault-tolerance capabilities and robustness of the tested hardware-implemented algorithm. © 2013 IEEE.

Mansour W.,TIMA Labs | Velazco R.,TIMA Labs | Ayoubi R.,University of Balamand | Ziade H.,Lebanese University | El Falou W.,Lebanese University
2013 25th International Conference on Microelectronics, ICM 2013 | Year: 2013

A fully automated fault-injection method is presented. It deals with transient faults resulting from the impact of energetic particles and it can be applied early at design phase, on any circuit for which the register transfer level model is available. Results issued from its application to an Artificial Neural Network benchmark application put in evidence the accuracy of the studied method to predict error rates due to transient faults generated by the radiation environment. © 2013 IEEE.

Mansour W.,TIMA Labs | Velazco R.,TIMA Labs | Ayoubi R.,University of Balamand | El Falou W.,Lebanese University | Ziade H.,Lebanese University
2013 3rd International Conference on Communications and Information Technology, ICCIT 2013 | Year: 2013

The associative Hopfield memory is a form of recurrent Artificial Neural Network (ANN) that can be used in applications such as pattern recognition, noise removal, information retrieval, and combinatorial optimization problems. In general, ANNs are considered as intrinsically fault-tolerant. A study of the capability of this algorithm to tolerate transient faults such as bit-flips provoked by the radiation environment is presented. Two software versions of the Hopfield Neural Network (HNN), one original and one fault-tolerant were implemented and executed by a LEON3 processor. Experimental results show the efficiency of the adopted strategy to tolerate faults that were injected at hardware level. © 2013 IEEE.

Artola L.,ONERA | Artola L.,French National Center for Space Studies | Velazco R.,TIMA Labs | Hubert G.,ONERA | And 7 more authors.
IEEE Transactions on Nuclear Science | Year: 2011

A method and the corresponding platform devoted to operational SEE-rate prediction are presented and illustrated by experimental results. Predicted error-rates are in well agreement with results issued from the activation of an SRAM platform, in 90 nm technology node, on board stratospheric balloons flights. Direct ionization of protons is investigated for a 65 SRAM memory virtually boarded on the balloon flight. © 2011 IEEE.

Mansour W.,TIMA Labs | Velazco R.,TIMA Labs
Journal of Electronic Testing: Theory and Applications (JETTA) | Year: 2013

Evaluating the sensibility of a given circuit with respect to soft errors became a main issue especially if it is intended to operate in space or at high altitudes. A hardware/software (HW/SW) approach to study the effects of soft errors by fault injection in the VHDL model of a CPU (Control Processor Unit) is presented and illustrated by results obtained for a LEON3 processor. The LEON3 is set to execute two benchmark algorithms. The first one is a typical 3x3 matrix multiplication, whereas the second one is a self-converging algorithm which is intended to provide correct results even if a failure occurs in the middle of the execution. The results of fault-injection campaigns targeting the register file unit of the processor are compared to those issued from a state-of-the-art method, the C.E.U. (Code Emulated Upset). One of the main advantages of the proposed method is the larger targeted Single Event Upset (SEU) sensitive area leading to improved error rate predictions. © 2013 Springer Science+Business Media New York.

Mansour W.,TIMA Labs. | Velazco R.,TIMA Labs. | El Falou W.,Lebanese University | Ziade H.,Lebanese University | Ayoubi R.,University of Balamand
2012 2nd International Conference on Advances in Computational Tools for Engineering Applications, ACTEA 2012 | Year: 2012

In this paper the consequences of SEU (Single Event Upset) faults on System on Chip devices (SOC) are studied. A PSOC microcontroller CY8C27643 manufactured by Cypress was chosen as a test vehicle. Fault injection sessions were performed using the so-called (Code Emulated Upset) approach in two different HW/SW environments. Obtained results put in evidence the potentially critical consequences of some of the faults occurring in the digital blocks when a matrix multiplication benchmark is being executed. © 2012 IEEE.

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