Ankur Mallick, Malhar Chaudhari*, Gauri Joshi
Carnegie Mellon University
* Oracle Corporation
We propose a rateless fountain coding strategy to alleviate the problem of straggling nodes – computing nodes that unpredictably slowdown or fail – in distributed matrix-vector multiplication. Our algorithm generates linear combinations of the m rows of the matrix, and assigns them to different worker nodes, which then perform row-vector products with the encoded rows. The original matrix-vector product can be decoded as soon as slightly more than m row-vector products are collectively completed by the nodes. This strategy enables fast nodes to steal work from slow nodes, without requiring the knowledge of node speeds. Compared to recently proposed fixed-rate erasure coding strategies which ignore partial work done by straggling nodes, rateless codes have a significantly lower overall delay, and a smaller computational overhead.
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