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End-to-End High Speed Forward Error Correction Using Graphics Processing Units

机译:使用图形处理单元端到端高速前进纠错

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Forward error correction (FEC) is an efficient error recovery mechanism for wireless networks in which erroneous packet is corrected in the destination node. More importantly, real-time and high-speed wireless networks require fast error recovery to ensure quality of service (QoS). Since graphics processing units (GPUs) offer massively parallel computing platform, we propose a GPU-based parallel error control mechanism using extended Hamming code supporting single-bit as well as multiple-bit error correction. We compare the performance of the proposed GPU-based approach with the equivalent sequential algorithm that runs on the traditional CPU for error strength, t, such that 1 ≤t≤7. Experimental results demonstrate that the proposed GPU-based approach outperforms the sequential approach in terms of execution time. Moreover, the proposed parallel implementation yields significant reduction in computational complexity from O(n~3) of the sequential algorithm to O(n) of the GPU-based approach, leading to tremendous speedup gain.
机译:向前纠错(FEC)是一种有效的错误恢复机制,用于无线网络,其中在目标节点中校正错误数据包。更重要的是,实时和高速无线网络需要快速恢复以确保服务质量(QoS)。由于图形处理单元(GPU)提供了大规模并行计算平台,因此我们使用支持单位的扩展汉明代码以及多位误差校正来提出基于GPU的并联误差控制机制。我们使用在传统CPU上运行的等效顺序算法进行比较基于GPU的方法的性能,以进行错误强度,使得1≤t≤7。实验结果表明,在执行时间方面,所提出的基于GPU的方法优于顺序方法。此外,所提出的并行实现产生的计算复杂度从顺序算法的o(n〜3)到基于GPU的方法的O(n)的计算复杂度显着降低,导致巨大的加速增益。

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