  The identification, and subsequent discovery, of fast radio transients
through blind-search surveys requires a large amount of processing power, in
worst cases scaling as $\mathcal{O}(N^3)$. For this reason, survey data are
generally processed offline, using high-performance computing architectures or
hardware-based designs. In recent years, graphics processing units have been
extensively used for numerical analysis and scientific simulations, especially
after the introduction of new high-level application programming interfaces.
Here we show how GPUs can be used for fast transient discovery in real-time. We
present a solution to the problem of de-dispersion, providing performance
comparisons with a typical computing machine and traditional pulsar processing
software. We describe the architecture of a real-time, GPU-based transient
search machine. In terms of performance, our GPU solution provides a speed-up
factor of between 50 and 200, depending on the parameters of the search.
