  A promising research area that has recently emerged, is on how to use index
coding to improve the communication efficiency in distributed computing
systems, especially for data shuffling in iterative computations. In this
paper, we posit that pliable index coding can offer a more efficient framework
for data shuffling, as it can better leverage the many possible shuffling
choices to reduce the number of transmissions. We theoretically analyze pliable
index coding under data shuffling constraints, and design a hierarchical
data-shuffling scheme that uses pliable coding as a component. We find benefits
up to $O(ns/m)$ over index coding, where $ns/m$ is the average number of
workers caching a message, and $m$, $n$, and $s$ are the numbers of messages,
workers, and cache size, respectively.
