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English(EN) ProWAFT: A ROMA-LPD Instance for Workload-Aware and Dynamic Fault Tolerance in FPGA-Based CNN Accelerators

新框架增强了FPGA加速器中的容错能力

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了ProWAFT，一个专为SRAM基FPGA上实现的CNN加速器设计的新型容错框架。该系统解决了瞬态故障带来的挑战，这些故障可能损害边缘计算环境的可靠性。ProWAFT利用部分重构，跨可重构分区动态应用三模冗余（TMR），平衡工作负载关键性、故障传播和重构开销，以优化延迟、能耗和可靠性。 AI

影响 增强了网络边缘AI推理硬件的可靠性，这对于实时应用至关重要。

排序理由 该条目是一篇学术论文，详细介绍了硬件加速器的新技术框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新框架增强了FPGA加速器中的容错能力

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该条目是一篇学术论文，详细介绍了硬件加速器的新技术框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Xinxin Chen, Haoran Qiao, Yiming Guo, Kecheng Luo, Siyuan Feng, Jingwen Ma ·

    ProWAFT：一种用于FPGA基CNN加速器中工作负载感知和动态容错的ROMA-LPD实例

    arXiv:2607.01602v1 Announce Type: new Abstract: SRAM-based FPGAs provide an attractive platform for energy- and latency-constrained CNN inference at the network edge, yet transient faults can lead to silent errors that compromise reliability. Always-on redundancy (e.g., full TMR)…

  2. arXiv cs.CL TIER_1 English(EN) · Jingwen Ma ·

    ProWAFT：用于 FPGA 加速器中基于工作负载感知和动态容错的 ROMA-LPD 实例

    SRAM-based FPGAs provide an attractive platform for energy- and latency-constrained CNN inference at the network edge, yet transient faults can lead to silent errors that compromise reliability. Always-on redundancy (e.g., full TMR) improves correctness but incurs substantial per…

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