Optimizing Scrubbing by Netlist Analysis for FPGA Configuration Bit Classification and Floorplanning

Existing scrubbing techniques for SEU mitigation on FPGAs do not guarantee an error-free operation after SEU recovering if the affected configuration bits do belong to feedback loops of the implemented circuits. In this paper, we a) provide a netlist-based circuit analysis technique to distinguish so-called critical configuration bits from essential bits in order to identify configuration bits which will need also state-restoring actions after a recovered SEU and which not. Furthermore, b) an alternative classification approach using fault injection is developed in order to compare both classification techniques. Moreover, c) we will propose a floorplanning approach for reducing the effective number of scrubbed frames and d), experimental results will give evidence that our optimization methodology not only allows to detect errors earlier but also to minimize the Mean-Time-To-Repair (MTTR) of a circuit considerably. In particular, we show that by using our approach, the MTTR for datapath-intensive circuits can be reduced by up to 48.5% in comparison to standard approaches

An Error-Detection and Self-Repairing Method for Dynamically and Partially Reconfigurable Systems

Reconfigurable systems are gaining an increasing interest in the domain of safety-critical applications, for example in the space and avionic domains. In fact, the capability of reconfiguring the system during run-time execution and the high computational power of modern Field Programmable Gate Arrays (FPGAs) make these devices suitable for intensive data processing tasks. Moreover, such systems must also guarantee the abilities of self-awareness, self-diagnosis and self-repair in order to cope with errors due to the harsh conditions typically existing in some environments. In this paper we propose a selfrepairing method for partially and dynamically reconfigurable systems applied at a fine-grain granularity level. Our method is able to detect, correct and recover errors using the run-time capabilities offered by modern SRAM-based FPGAs. Fault injection campaigns have been executed on a dynamically reconfigurable system embedding a number of benchmark circuits. Experimental results demonstrate that our method achieves full detection of single and multiple errors, while significantly improving the system availability with respect to traditional error detection and correction methods

Partial TMR in FPGAs Using Approximate Logic Circuits

TMR is a very effective technique to mitigate SEU effects in FPGAs, but it is often expensive in terms of FPGA resource utilization and power consumption. For certain applications, Partial TMR can be used to trade off the reliability with the cost of mitigation. In this work we propose a new approach to build Partial TMR circuits for FPGAs using approximate logic circuits. This approach is scalable, with a fine granularity, and can provide a flexible balance between reliability and overheads. The proposed approach has been validated by the results of fault injection experiments and proton irradiation campaigns.This work was supported in part by the Spanish Ministry of Economy and Competitiveness under contract ESP2015-68245-C4-1-P

Using Fine Grain Approaches for highly reliable Design of FPGA-based Systems in Space

Nowadays using SRAM based FPGAs in space missions is increasingly considered due to their flexibility and reprogrammability. A challenge is the devices sensitivity to radiation effects that increased with modern architectures due to smaller CMOS structures. This work proposes fault tolerance methodologies, that are based on a fine grain view to modern reconfigurable architectures. The focus is on SEU mitigation challenges in SRAM based FPGAs which can result in crucial situations

Analysis of design alternatives on using dynamic and partial reconfiguration in a space application

Some of the biggest concerns in space systems are power consumption and reliability due to the limited power generated by the system's energy harvesters and the fact that once deployed, it is almost impossible to perform maintenance or repairs. Another consideration is that during deployment, the high exposure to electromagnetic radiation can cause single event damage effects including SEUs, SEFIs, SETs and others. In order to mitigate these problems inherent to the space environment, a system with dynamic and partial reconfiguration capabilities is proposed. This approach provide s the flexibility to reconfigure parts of the FPGA while still in operation, thus making the system more flexible, fault tolerant and less power-consuming. In this paper, several partial reconfiguration approaches are proposed and compared in terms of device occupation, power consumption, reconfiguration speed and size of memory footprints

New Design Techniques for Dynamic Reconfigurable Architectures

L'abstract è presente nell'allegato / the abstract is in the attachmen

Reliability and Makespan Optimization of Hardware Task Graphs in Partially Reconfigurable Platforms

This paper addresses the problem of reliability and makespan optimization of hardware task graphs in reconfigurable platforms by applying fault tolerance (FT) techniques to the running tasks based on the exploration of the Pareto set of solutions. In the presented solution, in contrast to the existing approaches in the literature, task graph scheduling, tasks parallelism, reconfiguration delay, and FT requirements are taken into account altogether. This paper first presents a model for hardware task graphs, task prefetch and scheduling, reconfigurable computer, and a fault model for reliability. Then, a mathematical model of an integer nonlinear multi-objective optimization problem is presented for improving the FT of hardware task graphs, scheduled in partially reconfigurable platforms. Experimental results show the positive impacts of choosing the FT techniques selected by the proposed solution, which is named Pareto-based. Thus, in comparison to nonfault-tolerant designs or other state-of-the-art FT approaches, without increasing makespan, about 850% mean time to failure (MTTF) improvement is achieved and, without degrading reliability, makespan is improved by 25%. In addition, experiments in fault-varying environments have demonstrated that the presented approach outperforms the existing state-of-the-art adaptive FT techniques in terms of both MTTF and makespan