Fast Search Algorithms for Associative Memories
IEEE Transactions on Computers
The Maximum and Minimum Selector SELRAM and its Application for Developing Fast Sorting Machines
IEEE Transactions on Computers
Search algorithms for bi-sequential machines
Journal of Parallel and Distributed Computing
Algorithms for Parallel-Search Memories
Journal of the ACM (JACM)
An O(n+k) Algorithm for Ordered Retrieval from an Associative Memory
IEEE Transactions on Computers
A note on architectures for large-capacity CAMs
Integration, the VLSI Journal
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Several useful associative memory (AM) algorithms deal with identifying extreme values (max or min) in a specified field of a selected subset of words. Previously proposed algorithms for such extremes-value searches are bit-sequential in nature, even when implemented on fully parallel AMs. We show how the multiple-bit search capability of a fully parallel AM can be used to advantage in reducing the expected search time for finding extreme values. The idea is to search for the all-ones pattern within subfields of the specified search field in lieu of, or prior to, examining bit slices one at a time. Optimal subfield length is determined for fixed-size and variable-size bit groupings and the corresponding reduction in search time is quantified. The results are extended to rank-based selection where the jth largest or smallest value in a given field of a selected subset of words is to be identified. Analyses point to significant reduction in the average number of search cycles.