Abstract We use Category Theory to interpret the family of algorithms for inference of DFAs
that work by merging states. This interpretation allows us to characterize the structure of the …

Finite state automata are widely used in firewalls, data detection and content audit systems
to match complex sets of regular expressions in network packets. However, with the …

Abstract The Graphics Processing Unit (GPU) is a promising platform to implement Deep
Packet Inspection (DPI) due to the GPU's rich parallelism and programmability for high …

The Automata Processor (AP) accelerates applications from domains ranging from machine
learning to genomics. However, as a spatial architecture, it is unable to handle larger …

Dynamic graph traversals (DGTs) currently are widely used in many important application
domains, especially in this big-data era that urgently demands high-performance graph …

Graphics processing units (GPU) can be used to accelerate deep packet inspection.
However, the state transition tables used to implement deterministic finite automata are very …

Graphics processing units (GPU) have potential to speed up deep packet inspection (DPI)
by processing many packets in parallel. However, popular methods of DPI such as …

Graphics processing units (GPUs) have inadvertently become supercomputers in and of
themselves, to the benefit of applications outside of graphics. Acceleration of multiple orders …

Current network traffic analysis systems heavily rely on Deep Packet Inspection (DPI)
techniques, such as Finite Automata (FA), to detect patterns carried by regular expression …

The big-data era has brought new challenges to computer architectures due to the large-
scale computation and data. Moreover, this problem becomes critical in several domains …