Adaptive reconfigurable voting for enhanced reliability in medium-grained fault tolerant architectures

The impact of SRAM-based FPGAs is constantly growing in aerospace industry despite the fact that their volatile configuration memory is highly susceptible to radiation effects. Therefore, strong fault-handling mechanisms have to be developed in order to protect the design and make it capable of fighting against both soft and permanent errors. In this paper, a fully reconfigurable medium-grained triple modular redundancy (TMR) architecture which forms part of a runtime adaptive on-board processor (OBP) is presented. Fault mitigation is extended to the voting mechanism by applying our reconfiguration methodology not only to domain replicas but also to the voter itself. The proposed approach takes advantage of adaptive configuration placement and modular property of the OBP, thus allowing on-line creation of different medium-grained TMRs and selection of their granularity level. Consequently, we are able to narrow down the fault-affected area thus making the error recovery process faster and less power consuming. The conventional hardware based voting is supported by the ICAP-based one in order to additionally strengthen the reconfigurable intermediate voting. In addition, the implementation methodology ensures using only one memory footprint for all voters and their voting adaptations thus saving storing resources in expensive rad-hard memories

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

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

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

A new architecture for single-event upset detection & reconfiguration of SRAM-based FPGAs

Field Programmable Gate Arrays (FPGA) are used in a variety of applications, ranging from consumer electronics to devices in spacecrafts because of their flexibility in achieving requirements such as low cost, high performance, and fast turnaround. SRAM-based FPGAs can experience single bit flips in the configuration memory due to high-energy neutrons or alpha particles hitting critical nodes in the SRAM cells, by transferring enough energy to effect the change. High energy particles can be emitted by cosmic radiation or traces of radioactive elements in device packaging. The result of this could range from unwanted functional or data modification, data loss in the system, to damage to the cell where the charged particle makes impact. This phenomenon is known as a Single Event Upset (SEU) and makes fault tolerance a critical requirement in FPGA design. This research proposes a shift in architecture from current SRAM-based FPGAs such as Xilinx Virtex. The proposed architecture includes an inherent SEU detection through parity checking of the configuration memory. The inherent SEU detection sets a syndrome flag when an odd number of bit flips occur within a data frame of the configuration memory. To correct a fault, the FPGA the affected data frame is partially reconfigured. Existing and proposed solutions include: Triple Modular Redundancy (TMR) systems; readback and compare the configuration memory; and periodically reprogramming the entire configuration memory, also known as scrubbing. The advantages afforded by the proposed architecture over existing solutions include: faster error detection and correction latency over the readback method and better area and power overhead over TMR

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

A run time adaptive architecture to trade-off performance for fault tolerance applied to a DVB on-board processor

Reliability is one of the key issues in space applications. Although highly flexible and generally less expensive than predominantly used ASICs, SRAM-based FPGAs are very susceptible to radiation effects. Hence, various fault tolerant techniques have to be applied in order to handle faults and protect the design. This paper presents a reconfigurable on-board processor capable of run-time adaptation to harsh environmental conditions and different functional demands. Run-time reconfigurability is achieved applying two different reconfiguration methodologies. We propose a novel self-reconfigurable architecture able to on demand duplicate or triplicate part of the design in order to form DMR and TMR structures. Moreover, we introduce two different approaches for voting the correct output. The first one is a traditional voter that adapts to different DMR/TMR domain positions whereas the second implies comparing the captured flip-flop values directly from the configuration memory read through ICAP. The comparison is done periodically by an embedded processor thus completely excluding the voting mechanism in hardware. The proposed run-time reconfiguration methodology provides savings in terms of device utilization, reconfiguration time, power consumption and significant reductions in the amount of rad-hard memory used by partial configurations

Design techniques for xilinx virtex FPGA configuration memory scrubbers

SRAM-based FPGAs are in-field reconfigurable an unlimited number of times. This characteristic, together with their high performance and high logic density, proves to be very convenient for a number of ground and space level applications. One drawback of this technology is that it is susceptible to ionizing radiation, and this sensitivity increases with technology scaling. This is a first order concern for applications in harsh radiation environments, and starts to be a concern for high reliability ground applications. Several techniques exist for coping with radiation effects at user application. In order to be effective they need to be complemented with configuration memory scrubbing, which allows error mitigation and prevents failures due to error accumulation. Depending on the radiation environment and on the system dependability requirements, the configuration scrubber design can become more or less complex. This paper classifies and presents current and novel design methodologies and architectures for SRAM-based FPGAs, and in particular for Xilinx Virtex-4QV/5QV, configuration memory scrubbers

An Adaptive Modular Redundancy Technique to Self-regulate Availability, Area, and Energy Consumption in Mission-critical Applications

As reconfigurable devices\u27 capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing environments that require high degree of adaptation. The hardware layer is implemented on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA) to provide self-repair using a novel approach called a Reconfigurable Adaptive Redundancy System (RARS). The software layer supervises the organic activities within the FPGA and extends the self-healing capabilities through application-independent, intrinsic, evolutionary repair techniques to leverage the benefits of dynamic Partial Reconfiguration (PR). A SMART prototype is evaluated using a Sobel edge detection application. This prototype is shown to provide sustainability for stressful occurrences of transient and permanent fault injection procedures while still reducing energy consumption and area requirements. An Organic Genetic Algorithm (OGA) technique is shown capable of consistently repairing hard faults while maintaining correct edge detector outputs, by exploiting spatial redundancy in the reconfigurable hardware. A Monte Carlo driven Continuous Markov Time Chains (CTMC) simulation is conducted to compare SMART\u27s availability to industry-standard Triple Modular Technique (TMR) techniques. Based on nine use cases, parameterized with realistic fault and repair rates acquired from publically available sources, the results indicate that availability is significantly enhanced by the adoption of fast repair techniques targeting aging-related hard-faults. Under harsh environments, SMART is shown to improve system availability from 36.02% with lengthy repair techniques to 98.84% with fast ones. This value increases to five nines (99.9998%) under relatively more favorable conditions. Lastly, SMART is compared to twenty eight standard TMR benchmarks that are generated by the widely-accepted BL-TMR tools. Results show that in seven out of nine use cases, SMART is the recommended technique, with power savings ranging from 22% to 29%, and area savings ranging from 17% to 24%, while still maintaining the same level of availability

Fault and Defect Tolerant Computer Architectures: Reliable Computing With Unreliable Devices

This research addresses design of a reliable computer from unreliable device technologies. A system architecture is developed for a fault and defect tolerant (FDT) computer. Trade-offs between different techniques are studied and yield and hardware cost models are developed. Fault and defect tolerant designs are created for the processor and the cache memory. Simulation results for the content-addressable memory (CAM)-based cache show 90% yield with device failure probabilities of 3 x 10(-6), three orders of magnitude better than non fault tolerant caches of the same size. The entire processor achieves 70% yield with device failure probabilities exceeding 10(-6). The required hardware redundancy is approximately 15 times that of a non-fault tolerant design. While larger than current FT designs, this architecture allows the use of devices much more likely to fail than silicon CMOS. As part of model development, an improved model is derived for NAND Multiplexing. The model is the first accurate model for small and medium amounts of redundancy. Previous models are extended to account for dependence between the inputs and produce more accurate results