Associative IC memories with relational search and nearest-match capabilities

Jalaleddine, S.M.S.; Johnson, L.G.

doi:10.1109/4.135333

Cited by 15 publications

(4 citation statements)

References 36 publications

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“…In this context, there have been many studies and practical uses of CAM, including the above applications. Examples include cache tag tables, TLBs (translation lookaside buffers), which are tables used to speed up the conversion from logical addresses to physical addresses, neural networks, address filters, data compression, dictionary retrieval, and associative processors [2][3][4][5][6][7][8]. There are factors that hinder their practical use, such as the relation between processing speed and hardware complexity, and also the problem of cost.…”

Section: Introductionmentioning

confidence: 99%

A flexible multiport content-addressable memory

2006

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SUMMARYThis paper is concerned with content-addressable memory (CAM), which is a kind of functional memory. Flexible multiport content-addressable memory (FMCAM) is proposed, in which flexible retrieval functions and a multiport structure are realized. The implementation and an evaluation are presented. It is known that CAM offers high speed of the matching retrieval function. On the other hand, there are problems in practice concerning the relation between the processing speed and the number of comparators, and also the problem of cost, which have prevented its widespread use. Consequently, we developed the following FMCAM. Multiport CAM is realized by reducing the increase of the number of comparators while retaining highspeed matching retrieval functions. Functions for flexible retrieval can be added by implementation in an FPGA. By the categorization process and the use of a ring counter, multiple processing operations can be performed immediately while reducing the number of comparators. This improves the performance of the CAM itself. Another advantage is that FMCAM alone can perform the same processing in situations in which parallel CAM should be applied. After implementing the proposed FMCAM, several tests were performed for comparison. Excellent values were obtained: the AT product was 37.5% lower on average than in conventional CAM, and the increase in hardware complexity was by a factor of 1.57 even if the number of ports was increased by a factor of 4.

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Section: Introductionmentioning

confidence: 99%

A flexible multiport content-addressable memory

2006

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“…Current progress of IC technology resulted in successful ASIC designs of conventional single-comparand associative processors with extended search operations and memory cells designed on the transistor level [5,7,18,21]. Singlecomparand memories became embedded features of Spartan-II and Virtex programmable FPGA devices from Xilinx.…”

Section: Introductionmentioning

confidence: 99%

An FPGA Implementation of a Multi-comparand Multi-search Associative Processor

Kokosiński

Sikora

2002

Lecture Notes in Computer Science

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Abstract. The multi-comparand associative search paradigm is shown to be efficient in processing complex search problems from many application areas including computational geometry, graph theory, and list/matrix computations. In this paper the first FPGA implementation of a small multi-comparand multi-search associative processor is reported. The architecture of the processor and its functions are described in detail. The processor works in a combined bit-serial/bit-parallel mode. Its main component is a multi-comparand associative memory with up to 16 programmable prescription functions (logic searches). Parameters of implemented FPGA devices are presented and discussed.

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“…Practically important distance measures are the Hamming (data strings, voice patterns, black/white pictures) and the Manhattan (gray-scale or color pictures) distance. Previous methods for winner search have been based on: (a) analog neural networks [3], (b) SRAMs and a separate digital winner-take-all (WTA) circuit [4], (c) an analog WTA based on MOSFETs in source follower configuration [5] or a time-domain concept [6]. Problems of these solutions are: Large area-consumption [3,4,6] because the search circuits are of order R 2 (O(R 2 )) or O(R*W) complexity.…”

Section: Introductionmentioning

confidence: 99%