  Pattern Matching is a computationally intensive task used in many research
fields and real world applications. Due to the ever-growing volume of data to
be processed, and increasing link speeds, the number of patterns to be matched
has risen significantly. In this paper we explore the parallel capabilities of
modern General Purpose Graphics Processing Units (GPGPU) applications for high
speed pattern matching. A highly compressed failure-less Aho-Corasick algorithm
is presented for Intrusion Detection Systems on off-the-shelf hardware. This
approach maximises the bandwidth for data transfers between the host and the
Graphics Processing Unit (GPU). Experiments are performed on multiple alphabet
sizes, demonstrating the capabilities of the library to be used in different
research fields, while sustaining an adequate throughput for intrusion
detection systems or DNA sequencing. The work also explores the performance
impact of adequate prefix matching for alphabet sizes and varying pattern
numbers achieving speeds up to 8Gbps and low memory consumption for intrusion
detection systems.
