$\texttt{NeRCC}$: Nested-Regression Coded Computing for Resilient Distributed Prediction Serving Systems

Resilience against stragglers is a critical element of prediction serving systems, tasked with executing inferences on input data for a pre-trained machine-learning model. In this paper, we propose NeRCC, as a general straggler-resistant framework for approximate coded computing. NeRCC includes three layers: (1) encoding regression and sampling, which generates coded data points, as a combination of original data points, (2) computing, in which a cluster of workers run inference on the coded data points, (3) decoding regression and sampling, which …

computing cs.dc cs.it cs.lg data distributed element encoding framework general inferences machine math.it paper prediction regression resilience resilient sampling systems