  Distributed computation is a framework used to break down a complex
computational task into smaller tasks and distributing them among computational
nodes. Erasure correction codes have recently been introduced and have become a
popular workaround to the well known ``straggling nodes'' problem, in
particular, by matching linear coding for linear computation tasks. It was
observed that decoding tends to amplify the computation ``noise'', i.e., the
numerical errors at the computation nodes. We propose taking advantage of the
case that more nodes return than minimally required. We show how a clever
construction of a polynomial code, inspired by recent results on robust frames,
can significantly reduce the amplification of noise, and achieves graceful
degradation with the number of straggler nodes.
