Assessing Scrubbing Techniques for Xilinx SRAM-based FPGAs in Space Applications

SRAM-based FPGAs are becoming increasingly attractive for use in space applications due to their reconfigurability and signal processing capabilities, as well as their increasing speed and capacity. Traditional SRAM-based FPGAs, however, are highly sensitive to the ionizing radiation environment in space, making them prone to radiation-induced memory upsets. In this paper, we evaluate and compare scrubbing techniques for Xilinx SRAM-based FPGAs with respect to radiation-induced single event upsets. A test framework using an exchangeable payload is developed for this purpose and run on a Xilinx Virtex-5 FPGA. We show that recent SRAM-based FPGAs can constitute a cost-efficient alternative to radiation-hardened or antifuse FPGAs for non-critical space application such as satellite instruments

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

Area-driven partial reconfiguration for SEU mitigation on SRAM-based FPGAs

This paper presents an area-driven Field-Programmable Gate Array (FPGA) scrubbing technique based on partial reconfiguration for Single Event Upset (SEU) mitigation. The proposed method is compared with existing techniques such as blind and on-demand scrubbing on a novel SEU mitigation framework implemented on the ZYNQ platform, supporting various SEU and scrubbing rates. A design space exploration on the availability versus data transfers from a Double Data Rate Type 3 (DDR3) memory, shows that our approach outperforms blind scrubbing for a range of availability values when a second order polynomial IP is targeted. A comparison to an existing on-demand scrubbing technique based on Dual Modular Redundancy (DMR) shows that our approach saves up to 46% area for the same case study

Self-reference Scrubber for TMR Systems Based on Xilinx Virtex FPGAs

SRAM-based FPGAs are sensitive to radiation effects. Soft errors can appear and accumulate, potentially defeating mitigation strategies deployed at the Application Layer. Therefore, Configuration Memory scrubbing is required to improve radiation tolerance of such FPGAs in space applications. Virtex FPGAs allow runtime scrubbing by means of dynamic partial reconfiguration. Even with scrubbing, intra-FPGA TMR systems are subjected to common-mode errors affecting more than one design domain. This is solved in inter-FPGA TMR systems at the expense of a higher cost, power and mass. In this context, a self-reference scrubber for device-level TMR system based on Xilinx Virtex FPGAs is presented. This scrubber allows for a fast SEU/MBU detection and correction by peer frame comparison without needing to access a golden configuration memor

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 Tolerant Electronic System Design

Due to technology scaling, which means reduced transistor size, higher density, lower voltage and more aggressive clock frequency, VLSI devices may become more sensitive against soft errors. Especially for those devices used in safety- and mission-critical applications, dependability and reliability are becoming increasingly important constraints during the development of system on/around them. Other phenomena (e.g., aging and wear-out effects) also have negative impacts on reliability of modern circuits. Recent researches show that even at sea level, radiation particles can still induce soft errors in electronic systems. On one hand, processor-based system are commonly used in a wide variety of applications, including safety-critical and high availability missions, e.g., in the automotive, biomedical and aerospace domains. In these fields, an error may produce catastrophic consequences. Thus, dependability is a primary target that must be achieved taking into account tight constraints in terms of cost, performance, power and time to market. With standards and regulations (e.g., ISO-26262, DO-254, IEC-61508) clearly specify the targets to be achieved and the methods to prove their achievement, techniques working at system level are particularly attracting. On the other hand, Field Programmable Gate Array (FPGA) devices are becoming more and more attractive, also in safety- and mission-critical applications due to the high performance, low power consumption and the flexibility for reconfiguration they provide. Two types of FPGAs are commonly used, based on their configuration memory cell technology, i.e., SRAM-based and Flash-based FPGA. For SRAM-based FPGAs, the SRAM cells of the configuration memory highly susceptible to radiation induced effects which can leads to system failure; and for Flash-based FPGAs, even though their non-volatile configuration memory cells are almost immune to Single Event Upsets induced by energetic particles, the floating gate switches and the logic cells in the configuration tiles can still suffer from Single Event Effects when hit by an highly charged particle. So analysis and mitigation techniques for Single Event Effects on FPGAs are becoming increasingly important in the design flow especially when reliability is one of the main requirements