论文标题
分布式矩阵乘法的连续近似编码
Successive Approximation Coding for Distributed Matrix Multiplication
论文作者
论文摘要
最近引入了编码的分布式计算，以减轻散乱者对分布式计算的影响。本文将近似计算的想法与编码计算结合在一起，以进一步加速计算。我们提出了连续的近似编码（SAC）技术，以实现准确性和速度之间的权衡，从而使分布式计算系统产生近似值随着时间的推移而提高准确性的近似值。如果足够数量的计算节点完成了任务，则SAC精确地恢复了所需的计算。从理论上讲，我们为我们的SAC技术提供了设计指南，并且从数值上表明，与以前的方法相比，SAC实现了更好的准确速度折衷。
Coded distributed computing was recently introduced to mitigate the effect of stragglers on distributed computing. This paper combines ideas of approximate computing with coded computing to further accelerate computation. We propose successive approximation coding (SAC) techniques that realize a tradeoff between accuracy and speed, allowing the distributed computing system to produce approximations that increase in accuracy over time. If a sufficient number of compute nodes finish their tasks, SAC exactly recovers the desired computation. We theoretically provide design guidelines for our SAC techniques, and numerically show that SAC achieves a better accuracy-speed tradeoff in comparison with previous methods.
