  The problem of searching for unmodeled gravitational-wave bursts can be
thought of as a pattern recognition problem: how to find statistically
significant clusters in spectrograms of strain power when the precise signal
morphology is unknown. In a previous publication, we showed how "seedless
clustering" can be used to dramatically improve the sensitivity of searches for
long-lived gravitational-wave transients. In order to manage the computational
costs, this initial analysis focused on externally triggered searches where the
source location and emission time are both known to some degree of precision.
In this paper, we show how the principle of seedless clustering can be extended
to facilitate computationally-feasible, all-sky searches where the direction
and emission time of the source are entirely unknown. We further demonstrate
that it is possible to achieve a considerable reduction in computation time by
using graphical processor units (GPUs), thereby facilitating more sensitive
searches.
