4 research outputs found

    An adaptive method to tolerate soft errors in SRAM-based FPGAs

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    AbstractIn this paper, we present an adaptive method that is a combination of SEU-avoidance in CAD flow and adaptive redundancy to tolerate soft error effects in SRAM-based FPGAs. This method is based on the modification of T-VPack and VPR tools. Three different steps of these tools are modified for SEU-awareness: (1) clustering, (2) placement and (3) routing. Then we use the unused resources as redundancy. We have investigated the effect of this method on several MCNC benchmarks. This investigation has been performed using three experiments: (1) SEU-awareness in clustering with redundancy, (2) SEU-awareness in clustering and placement with redundancy and (3) SEU-awareness in clustering, placement and routing with redundancy. With a confidence level of 95%, the results show that, using each of these three experiments, the system failure rate of ten MCNC circuits has been decreased between 4.52% and 10.42%, between 10.25% and 21.63%, and between 10.48% and 24.39%, respectively

    SRAM-Based FPGA Systems for Safety-Critical Applications: A Survey on Design Standards and Proposed Methodologies

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    As the ASIC design cost becomes affordable only for very large-scale productions, the FPGA technology is currently becoming the leading technology for those applications that require a small-scale production. FPGAs can be considered as a technology crossing between hardware and software. Only a small-number of standards for the design of safety-critical systems give guidelines and recommendations that take the peculiarities of the FPGA technology into consideration. The main contribution of this paper is an overview of the existing design standards that regulate the design and verification of FPGA-based systems in safety-critical application fields. Moreover, the paper proposes a survey of significant published research proposals and existing industrial guidelines about the topic, and collects and reports about some lessons learned from industrial and research projects involving the use of FPGA devices

    A theory of robust software synthesis

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    A key property for systems subject to uncertainty in their operating environment is robustness, ensuring that unmodelled, but bounded, disturbances have only a proportionally bounded effect upon the behaviours of the system. Inspired by ideas from robust control and dissipative systems theory, we present a formal definition of robustness and algorithmic tools for the design of optimally robust controllers for omega-regular properties on discrete transition systems. Formally, we define metric automata - automata equipped with a metric on states - and strategies on metric automata which guarantee robustness for omega-regular properties. We present fixed point algorithms to construct optimally robust strategies in polynomial time. In contrast to strategies computed by classical graph theoretic approaches, the strategies computed by our algorithm ensure that the behaviours of the controlled system gracefully degrade under the action of disturbances; the degree of degradation is parameterized by the magnitude of the disturbance. We show an application of our theory to the design of controllers that tolerate infinitely many transient errors provided they occur infrequently enough
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