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Fast BCH syndrome generator using parallel polynomial division algorithm for GPGPUs

机译:GPGPU使用并行多项式除法的快速BCH综合症发生器

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Recent developments in General Purpose Graphical Processing Units (GPGPU) has attracted many researchers to invent new methods to decode errors for linear block codes such as Bose-Chaudhuri-Hocquenghem (BCH), and Reed Solomon (RS) codes. In this paper, we propose a parallel polynomial division algorithm to compute the syndromes of a received BCH code. Further, using the parallel thread technique offered by the GPGPUs, we propose to use the same to generate the parity bits of the BCH encoder. We have devised an engine to compute the syndromes for BCH codes with field extension m=15, and we studied the GPU implementation of the same for bit errors t=2..15. The results, when compared against the conventional syndrome generator, has a minimum of 12% improvement in the efficiency of the syndrome generator kernel routines. Hence, this method provides an efficient way to compute syndromes for a programmable error correction mode.
机译:通用图形处理单元(GPGPU)的最新发展吸引了许多研究人员发明新的方法来解码线性块代码的错误,例如Bose-Chaudhuri-Hocquenghem(BCH)和Reed Solomon(RS)代码。在本文中,我们提出了一种并行多项式除法算法来计算接收到的BCH码的校验子。此外,建议使用GPGPU提供的并行线程技术来生成BCH编码器的奇偶校验位。我们设计了一种引擎来计算字段扩展为m = 15的BCH码的校验子,并且针对比特错误t = 2..15研究了相同的GPU实现。与常规校正子生成器相比,结果使校正子生成器内核例程的效率至少提高了12%。因此,该方法提供了一种有效的方式来计算可编程纠错模式的校正子。

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