• Nuclear Engineering and Technology
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• 제54권6호
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• pp.2031-2036
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• 2022

Energetic particle strikes the device and induces data corruption in the configuration memory (CRAM), causing errors and even malfunctions in a system on chip (SoC). Software-based fault injection is a convenient way to assess device performance. In this paper, dynamic partial reconfiguration (DPR) is adopted to make fault injection on a Xilinx 16 nm FinFET Ultrascale+ MPSoC. And the reconfiguration module implements the Sobel and Gaussian image filtering, respectively. Fault injections are executed on the static and reconfiguration modules' bitstreams, respectively. Another contribution is that the failure modes and effects analysis (FMEA) method is applied to evaluate the system reliability, according to the obtained injection results. This paper proposes a software-based solution to estimate programmable device vulnerability.

• 센서학회지
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• 제32권4호
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• pp.246-251
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• 2023

Internet of Things (IoT) systems process signals from various sensors using signal processing algorithms suitable for the signal characteristics. To analyze complex signals, these systems usually use signal processing algorithms in the frequency domain, such as fast Fourier transform (FFT), filtering, and short-time Fourier transform (STFT). In this study, we propose a multi-mode sensor signal processor (SSP) accelerator with an FFT-based hardware design. The FFT processor in the proposed SSP is designed with a radix-2 single-path delay feedback (R2SDF) pipeline architecture for high-speed operation. Moreover, based on this FFT processor, the proposed SSP can perform filtering and STFT operation. The proposed SSP is implemented on a field-programmable gate array (FPGA). By sharing the FFT processor for each algorithm, the required hardware resources are significantly reduced. The proposed SSP is implemented and verified on Xilinxh's Zynq Ultrascale+ MPSoC ZCU104 with 53,591 look-up tables (LUTs), 71,451 flip-flops (FFs), and 44 digital signal processors (DSPs). The FFT, filtering, and STFT algorithm implementations on the proposed SSP achieve 185x average acceleration.