LT Codes with Feedback: Accelerate the Distributed Matrix-Vector Multiplication with Stragglers

In this paper, we propose a coding scheme for distributed matrix-vector multiplication that builds upon the Luby transform (LT) codes with feedback. The ideal soliton distribution is utilized in our LT coding scheme to encode the sub-matrices. Besides, the belief propagation (BP) decoding algorithm is modified to cooperate with the feedback information. Compared with other coded distributed computations with straggling servers, our approach achieves lower computation latency when the overall delay incurred by the encoding, mapping and decoding process is considered. Furthermore, we compare the storage loads of different schemes and show that the LT coding with feedback has a strong comparative advantage in these straggler-tolerant computation scenarios.