Group-Wise Coding for Coded Distributed Computing Systems with Group Heterogeneity and Communication Delay

In distributed computing, coding techniques are shown to be an effective solution for mitigating the impact of stragglers. However, previous research on coding has predominantly focused on homogeneous worker environments, overlooking the fact that real-world systems often consist of heterogeneous workers with varying computing and communication capabilities. Specifically, uniform load allocation, without considering worker heterogeneity, can result in substantial latency losses. In this paper, we propose a load allocation strategy designed for distributed systems with group heterogeneity, where workers in the same group have similar computing and communication capabilities, but workers of different groups do not. By exploring group-wise MDS codes, we determine the optimal code dimension and optimal computation loads for individual groups. Our proposed approach demonstrates comparable computation times to existing methods, while exhibiting the advantage of much shorter encoding and decoding times.