Abstract: An engine architecture for processing finite automata includes a hyper non-deterministic automata (HNA) processor specialized for non-deterministic finite automata (NFA) processing. The HNA processor includes a plurality of super-clusters and an HNA scheduler. Each super-cluster includes a plurality of clusters. Each cluster of the plurality of clusters includes a plurality of HNA processing units (HPUs). A corresponding plurality of HPUs of a corresponding plurality of clusters of at least one selected super-cluster is available as a resource pool of HPUs to the HNA scheduler for assignment of at least one HNA instruction to enable acceleration of a match of at least one regular expression pattern in an input stream received from a network.

Abstract: An engine architecture for processing finite automata includes a hyper non-deterministic automata (HNA) processor specialized for non-deterministic finite automata (NFA) processing. The HNA processor includes a plurality of super-clusters and an HNA scheduler. Each super-cluster includes a plurality of clusters. Each cluster of the plurality of clusters includes a plurality of HNA processing units (HPUs). A corresponding plurality of HPUs of a corresponding plurality of clusters of at least one selected super-cluster is available as a resource pool of HPUs to the HNA scheduler for assignment of at least one HNA instruction to enable acceleration of a match of at least one regular expression pattern in an input stream received from a network.

Abstract: Matching at least one regular expression pattern in an input stream may be optimized by initializing a search context in a run stack based on (i) partial match results determined from walking segments of a payload of a flow through a first finite automation and (ii) a historical search context associated with the flow. The search context may be modified via push or pop operations to direct at least one processor to walk segments of the payload through the at least one second finite automation. The search context may be maintained in a manner that obviates overflow of the search context and obviating stalling of the push or pop operations to increase match performance.

Abstract: An engine architecture for processing finite automata includes a hyper non-deterministic automata (HNA) processor specialized for non-deterministic finite automata (NFA) processing. The HNA processor includes a plurality of super-clusters and an HNA scheduler. Each super-cluster includes a plurality of clusters. Each cluster of the plurality of clusters includes a plurality of HNA processing units (HPUs). A corresponding plurality of HPUs of a corresponding plurality of clusters of at least one selected super-cluster is available as a resource pool of HPUs to the HNA scheduler for assignment of at least one HNA instruction to enable acceleration of a match of at least one regular expression pattern in an input stream received from a network.

Abstract: Matching at least one regular expression pattern in an input stream may be optimized by initializing a search context in a run stack based on (i) partial match results determined from walking segments of a payload of a flow through a first finite automation and (ii) a historical search context associated with the flow. The search context may be modified via push or pop operations to direct at least one processor to walk segments of the payload through the at least one second finite automation. The search context may be maintained in a manner that obviates overflow of the search context and obviating stalling of the push or pop operations to increase match performance.

Abstract: An engine architecture for processing finite automata includes a hyper non-deterministic automata (HNA) processor specialized for non-deterministic finite automata (NFA) processing. The HNA processor includes a plurality of super-clusters and an HNA scheduler. Each super-cluster includes a plurality of clusters. Each cluster of the plurality of clusters includes a plurality of HNA processing units (HPUs). A corresponding plurality of HPUs of a corresponding plurality of clusters of at least one selected super-cluster is available as a resource pool of HPUs to the HNA scheduler for assignment of at least one HNA instruction to enable acceleration of a match of at least one regular expression pattern in an input stream received from a network.