  Graphics Processing Units allow for running massively parallel applications
offloading the CPU from computationally intensive resources, however GPUs have
a limited amount of memory. In this paper a trie compression algorithm for
massively parallel pattern matching is presented demonstrating 85% less space
requirements than the original highly efficient parallel failure-less
aho-corasick, whilst demonstrating over 22 Gbps throughput. The algorithm
presented takes advantage of compressed row storage matrices as well as shared
and texture memory on the GPU.
