  Despite significant progress in the caching literature concerning the worst
case and uniform average case regimes, the algorithms for caching with
nonuniform demands are still at a basic stage and mostly rely on simple
grouping and memory-sharing techniques. In this work we introduce a novel
centralized caching strategy for caching with nonuniform file popularities. Our
scheme allows for assigning more cache to the files which are more likely to be
requested, while maintaining the same sub-packetization for all the files. As a
result, in the delivery phase it is possible to perform linear codes across
files with different popularities without resorting to zero-padding or
concatenation techniques. We will describe our placement strategy for arbitrary
range of parameters. The delivery phase will be outlined for a small example
for which we are able to show a noticeable improvement over the state of the
art.
