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 Error-Detection and Self-Repairing Method for Dynamically and Partially Reconfigurable Systems / SONZA REORDA, Matteo; Sterpone, Luca; Ullah, Anees. - In: IEEE TRANSACTIONS ON COMPUTERS. - ISSN 0018-9340. - ELETTRONICO. - 66:6(2017), pp. 1022-1033. [10.1109/TC.2016.2607749]

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

SONZA REORDA, Matteo;STERPONE, LUCA;ULLAH, ANEES
2017

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2658319
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