Parallel Pattern Detection Engine

Abstract

A parallel pattern detection engine (PPDE) comprise multiple processing units (PUs) customized to do various modes of pattern recognition. The PUs are loaded with different patterns and the input data to be matched is provided to the PUs in parallel. Each pattern has an Opcode that defines what action to take when a particular data in the input data stream either matches or does not match the corresponding data being compared during a clock cycle. Each of the PUs communicate selected information so that PUs may be cascaded to enable longer patterns to be matched or to allow more patterns to be processed in parallel for a particular input data stream.

Description

CROSS REFERENCE TO RELATED APPLICATIONS [0001] The present invention is related to the following U.S. patent applications which are incorporated herein by reference: [0002] Ser. No. ______ (Attorney Docket No. RPS920030020US1) entitled “A Configurable Bi-Directional Bus For Communicating Between Autonomous Units” filed ______; and [0003] Ser. No. ______ (Attorney Docket No. RPS920030037US1) entitled “Intrusion Detection Using A Network Processor And A Parallel Pattern Detection Engine” filed ______.TECHNICAL FIELD [0004] The present invention relates in general to methods and systems for performing fast partial or exact pattern matching. BACKGROUND INFORMATION [0005] Recognizing patterns within a set of data is important in many fields, including speech recognition, image processing, seismic data, etc. Some image processors collect image data and then pre-process the data to prepare it to be correlated to reference data. Other systems, like speech recognition, are real time where th...

AI Technical Summary

Benefits of technology

This solution significantly enhances pattern matching speed and reduces storage needs, enabling efficient handling of large numbers of patterns and variable lengths, while allowing for exact, fuzzy, and longest match detection, thus overcoming the limitations of existing systems.

Problems solved by technology

In non-aligned data streams, there are some situations where patterns may be missed if only a single byte-by-byte comparison is implemented.

Since a library of RPs may be quite large, the processing required may be considerable.

Processing in small parallel processing units may be limited by the storage size required for the RPs.

Portable, inexpensive processing systems for chemical analysis, biological analysis, etc., may also be limited by the amount of storage needed to quickly process large numbers of RPs.

Pattern detection or recognition is a bottleneck in many applications today and software solutions cannot achieve the necessary performance.

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