  Modern computationally-heavy applications are often time-sensitive, demanding
distributed strategies to accelerate them. On the other hand, distributed
computing suffers from the bottleneck of slow workers in practice. Distributed
coded computing is an attractive solution that adds redundancy such that a
subset of distributed computations suffices to obtain the final result.
However, the final result is still either obtained within a desired time or
not, and for the latter, the resources that are spent are wasted. In this
paper, we introduce the novel concept of layered-resolution distributed coded
computations such that lower resolutions of the final result are obtained from
collective results of the workers -- at an earlier stage than the final result.
This innovation makes it possible to have more effective deadline-based
systems, since even if a computational job is terminated because of timing, an
approximated version of the final result can be released. Based on our
theoretical and empirical results, the average execution delay for the first
resolution is notably smaller than the one for the final resolution. Moreover,
the probability of meeting a deadline is one for the first resolution in a
setting where the final resolution exceeds the deadline almost all the time,
reducing the success rate of the systems with no layering.
