Abstract
Radiation tolerance in FPGAs is an important field of research particularly for reliable computation in electronics used in aerospace and satellite missions. The motivation behind this research is the degradation of reliability in FPGA hardware due to single-event effects caused by radiation particles. Redundancy is a commonly used technique to enhance the fault-tolerance capability of radiation-sensitive applications. However, redundancy comes with an overhead in terms of excessive area consumption, latency, and power dissipation. Moreover, the redundant circuit implementations vary in structure and resource usage with the redundancy insertion algorithms as well as number of used redundant stages. The radiation environment varies during the operation time span of the mission depending on the orbit and space weather conditions. Therefore, the overheads due to redundancy should also be optimized at run-time with respect to the current radiation level. In this paper, we propose a technique called Dynamic Reliability Management (DRM) that utilizes the radiation data, interprets it, selects a suitable redundancy level, and performs the run-time reconfiguration, thus varying the reliability levels of the target computation modules. DRM is composed of two parts. The design-time tool flow of DRM generates a library of various redundant implementations of the circuit with different magnitudes of performance factors. The run-time tool flow, while utilizing the radiation/error-rate data, selects a required redundancy level and reconfigures the computation module with the corresponding redundant implementation. Both parts of DRM have been verified by experimentation on various benchmarks. The most significant finding we have from this experimentation is that the performance can be scaled multiple times by using partial reconfiguration feature of DRM, e.g., 7.7 and 3.7 times better performance results obtained for our data sorter and matrix multiplier case studies compared with static reliability management techniques. Therefore, DRM allows for maintaining a suitable trade-off between computation reliability and performance overhead during run-time of an application.
Highlights
Research ArticleReceived 13 November 2019; Revised February 2020; Accepted May 2020; Published 13 June 2020
Background and Related Workwe describe the basic implementation strategy of triple modular redundancy (TMR) in Field Programmable Gate Arrays (FPGAs) followed by an insight into different forms of TMR and its cascaded version
We describe the need for building an adaptive system for optimizing reliability-performance trade-off for redundant FPGA hardware, at run-time, based on the radiation strength of the environment
Summary
Received 13 November 2019; Revised February 2020; Accepted May 2020; Published 13 June 2020. E run-time tool flow, while utilizing the radiation/error-rate data, selects a required redundancy level and reconfigures the computation module with the corresponding redundant implementation. Both parts of DRM have been verified by experimentation on various benchmarks. For rather short-term space missions, Single-Event Effects (SEEs) cause temporary errors to appear in the circuit whose mitigation strategies vary from internal masking (using redundancy) to system-reset requirement. DRM, based on the partial reconfiguration of FPGAs, is beneficial as it allows for the optimization of the performance overheads and, can save cost and power or free hardware resources for other tasks when feasible. E contribution of this paper lies around providing a complete approach for using SRAM-based FPGAs in space missions whereby using real-time radiation scenarios for our
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