Finite State Automata are widely used to accelerate pattern matching in many emerging
application domains like DNA sequencing and XML parsing. Conventional CPUs and …

High-performance automata-processing engines are traditionally evaluated using a limited
set of regular expression-rulesets. While regular expression rulesets are valid real-world …

Finite State Machines (FSM) are widely used computation models for many application
domains. These embarrassingly sequential applications with irregular memory access …

Automata Processing is an important kernel for many application domains, and is
challenging to accelerate using general purpose, von Neumann computers. New research …

Automata processing has seen a resurgence in importance due to its usefulness for pattern
matching and pattern mining of" big data." While large-scale automata processing is known …

We present a general automata processing framework on FPGAs, which generates an RTL
kernel for automata processing together with an AXI and PCIe based I/O circuitry. We …

Accelerating finite-state automata benefits several emerging application domains that are
built on pattern matching. In-memory architectures, such as the Automata Processor (AP) …

Newly-available spatial architectures to accelerate finite-automata processing have spurred
research and development on novel automata-based applications. However, spatial …

Mining complex patterns with hierarchical structures becomes more and more important to
understand the underlying information in large and unstructured databases. When …

The subset encoding method and related automata designs for improving the space
efficiency for many applications on the Automata Processor (AP) are presented. The method …