Netlogic Microsystems, Inc

Broadcom Corporation

Greg Watson

Sandeep Khanna

Varadarajan Srinivasan

Chetan Deshpande

Cristian Estan

Carl Gyllenhammer

Venkat Gaddam

Alexei Starovoitov

Mark Birman

Kumaravel Senniappan

A content search system for determining whether an input string matches one or more of a number of patterns embodied by a deterministic finite automaton (DFA) includes a plurality of DFA engines that simultaneously compare sequential overlapping segments of the input string. The overlap region shared by adjacent pairs of input string segments is of a predetermined size. Initially, the first DFA engine is designated as the master engine, and the remaining DFA engines are designated as slave engines whose state results are speculative. Resolution logic compares the state results of the master engine with the state results of the adjacent slave engine to selectively validate the state results of the successor engine, which upon validation becomes the new master engine.

Content search system including multiple deterministic finite automaton engines having shared memory resources

A method and apparatus are disclosed for determining whether an input string of characters matches a pattern. The pattern has the form of an activator expression, a counter expression, and a tail. The method involves monitoring one or more active states associated with the pattern, and comparing each character to the activator expression and the counter expression for each of the one or more active states. An input character match to the activator expression comprises an activator match, and a character match to the counter expression without matching the activator expression comprises a non-activator match. The number of one or more active states corresponds to the number of non-activator to activator character transitions between adjacent received matching characters.

Minimizing state lists for non-deterministic finite state automatons

A content search system for determining whether an input string matches one or more rules includes a parser, a rules database, and a search engine. The parser, which has an input to receive the input string, is to extract one or more selected portions of the input string to form a filtered input string, and is to generate a rule select signal in response to the selected portions of the input string. The rules database stores a plurality of sets of rules. The search engine is to compare the filtered input string with a selected set of rules selected in response to the rule select signal.

Targeted search system with de-obfuscating functionality

A content search system includes multiple pipelined search engines that implement different portions of a regular expression search operations. For some embodiments, the search pipeline includes a DFA engine, an NFA engine, and a token stitcher that combines partial match results generated by the DFA and NFA engines in a manner that prevents either engine from becoming a bottleneck. In addition, the token stitcher can be configured to implement unbounded sub-expressions without utilizing resources of the DFA or NFA engines.

Content search system having pipelined engines and a token stitcher

A system and method are disclosed that compiles a sub-expression associated with an inexact pattern contained in a regular expression into a plurality of microprogram instructions that can be stored in contiguous locations of an instruction memory. At least one of the microprogram instructions includes a next instruction address and a fetch length value, where the next instruction address indicates the instruction memory address of the next instruction to be executed and the fetch length value indicates the number of sequentially-executed instructions that are to be fetched from contiguous locations of the instruction memory.

Compact instruction format for content search systems

The power consumption of a search engine such as a CAM device is dynamically adjusted to prevent performance degradation and/or damage resulting from overheating. For some embodiments, the CAM device is continuously sampled to generate sampling signals indicating the number of active states and number of compare operations performed during each sampling period. The sampling signals are accumulated to generate an estimated device power profile, which is compared with reference values corresponding to predetermined power levels to generate a dynamic power control signal indicating predicted increases in the device's operating temperature resulting from its power consumption. The dynamic power control signal is then used to selectively reduce the input data rate of the CAM device, thereby reducing power consumption and allowing the device to cool.

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Palo Alto, CA, United States of America

Greg Watson