Table establishing and lookup method applied to network processor

Abstract

The invention provides a table establishing and lookup method applied to a network processor. According to the method, different types of hash tables are established and adopted, and the tables are unrelated and subjected to independent two-stage lookup. The method comprises the following steps: establishing different types of hash tables according to the size of the entry of the tables to be established; allocating different memory spaces to each table; assigning the size of the tables as well as first addresses; obtaining a search key, the type of a lookup table, and the first address of the table according to information extracted from a message during looking up; performing twice hash conversion on the key at the same time, wherein in the primary conversion process, the key is converted into an offset address to determine to determine an index value of the key in an index table, and in the secondary conversion process, the key is converted into a label to distinguish conflict items; reading content from a result table according to the index value to realize matching, so as to obtain a searched result. The method effectively reduces the access number of a memory, and further improves the look-up speed of the network processor and the resource utilization rate of the memory.

Description

technical field [0001] The invention relates to the field of network communication, in particular to a table building and searching method for a network processor. Background technique [0002] With the continuous improvement of the Internet speed, the continuous increase of network traffic and the continuous increase of the number of routing table entries, the efficiency of table lookup has become more and more the bottleneck of the performance of network processor equipment. There are two main factors that affect the efficiency of table lookup: one is the structure of the table, that is, the method of building the table, and the other is the method of table lookup, that is, to obtain a faster table lookup speed with as few storage resources as possible. [0003] In traditional data structures, such as linear tables, tries, etc., the relative position of records in the structure is random, and there is no definite relationship with the key of the record, and a large number ...

AI Technical Summary

Problems solved by technology

However, at this time, there will still be 4% of the keys that need to be looked up again. Usually, it will take up to 10 or more times to resolve these conflicting keys.

And usually in this case, the filling rate of the hash table corresponding to each lookup can only reach about 20%, which means that the probability of a storage location being filled with a key is only 20%, thus wasting 80% of storage resources

Therefore, the existing data structure table building and table lookup methods have the disadvantages of many lookup times, slow table lookup speed, and waste of storage resources

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