  At the Large Hadron Collider (LHC), the trigger systems for the detectors
must be able to process a very large amount of data in a very limited amount of
time, so that the nominal collision rate of 40 MHz can be reduced to a data
rate that can be stored and processed in a reasonable amount of time. This need
for high performance places very stringent requirements on the complexity of
the algorithms that can be used for identifying events of interest in the
trigger system, which potentially limits the ability to trigger on signatures
of various new physics models. In this paper, we present an alternative
tracking algorithm, based on the Hough transform, which avoids many of the
problems associated with the standard combinatorial track finding currently
used. The Hough transform is also well-adapted for Graphics Processing Unit
(GPU)-based computing, and such GPU-based systems could be easily integrated
into the existing High-Level Trigger (HLT). This algorithm offers the ability
to trigger on topological signatures of new physics currently not practical to
reconstruct, such as events with jets or black holes significantly displaced
from the primary vertex. This paper presents, for the first time, an
implementation and preliminary performance results using NVIDIA Tesla C2075 and
K20c GPUs.
