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Factored LT and Factored Raptor Codes for Large-Scale Distributed Matrix Multiplication

机译:大规模分布式矩阵乘法的因数LT和因数猛禽代码

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We propose two coding schemes for distributed matrix multiplication in the presence of stragglers. These coding schemes are adaptations of LT codes and Raptor codes to distributed matrix multiplication and are termed Factored LT (FLT) codes and Factored Raptor (FR) codes. Empirically, we show that FLT codes have a near-optimal recovery threshold when the number of worker nodes is very large, and that FR codes have an excellent recovery threshold while the number of worker nodes is moderately large. FLT and FR codes have better recovery thresholds when compared to Product codes and they are expected to have better numerical stability when compared to Polynomial codes, while they can also be decoded with a low-complexity decoding algorithm.
机译:我们提出了在存在散乱者的情况下用于分布式矩阵乘法的两种编码方案。这些编码方案是LT码和Raptor码对分布式矩阵乘法的适应,并被称为分解LT(FLT)码和分解Raptor(FR)码。根据经验,我们显示出当工作节点数量很大时,FLT代码具有接近最佳的恢复阈值;而当工作节点数量适中时,FR代码具有出色的恢复阈值。与乘积码相比,FLT和FR码具有更好的恢复阈值,与多项式码相比,它们具有更好的数值稳定性,同时还可以使用低复杂度解码算法对其进行解码。

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