Li {\it et al}. introduced coded distributed computing (CDC) scheme to reduce the communication load in general distributed computing frameworks such as MapReduce. They also proposed cascaded CDC schemes where each output function is computed multiple times, and proved that such schemes achieved the fundamental trade-off between computation load and communication load. However, these schemes require exponentially large numbers of input files and output functions when the number of computing nodes gets large. In this paper, by using the structure of placement delivery arrays (PDAs), we construct several infinite classes of cascaded CDC schemes. We also show that the numbers of output functions in all the new schemes are only a factor of the number of computing nodes, and the number of input files in our new schemes is much smaller than that of input files in CDC schemes derived by Li {\it et al}.
翻译:Li {it et al}. 引入了编码分布式计算(CDC) 计划,以减少一般分布式计算框架(如MapReduce)中的通信负荷。他们还提出了连锁计算式计算式计算式计算式计算式计算式计算式计算法(CDC)计划,其中每个输出函数都多次计算,并证明这种计划实现了计算式负载和通信负载之间的基本平衡。然而,当计算节点数量大时,这些计划需要大量输入式文件和输出功能。在本文中,我们通过定位交付阵列(PDAs)的结构,构建了数类无穷无穷的连锁计算式计算式计算式计算式计算式计算法。我们还表明,所有新计划的产出函数数量只是计算节点数的一个因素,而我们新计划中的投入文件数量远远小于由Li {it et al} 生成的CDC 计划中输入文件的数量。