  We present a novel gravitational wave detection algorithm that conducts a
matched filter search stochastically across the compact binary parameter space
rather than relying on a fixed bank of template waveforms. This technique is
competitive with standard template-bank-driven pipelines in both computational
cost and sensitivity. However, the complexity of the analysis is simpler
allowing for easy configuration and horizontal scaling across heterogeneous
grids of computers. To demonstrate the method we analyze approximately one
month of public LIGO data from July 27 00:00 2017 UTC - Aug 25 22:00 2017 UTC
and recover eight known confident gravitational wave candidates. We also inject
simulated binary black hole (BBH) signals to demonstrate the sensitivity.
