基于fpga的bram的深度和窄二进制内容可寻址存储器

Ameer Abdelhadi, G. Lemieux
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引用次数: 9

摘要

二进制内容可寻址存储器(BCAMs)是一种大规模并行搜索引擎,能够在一个时钟周期内搜索整个内存空间。bcam广泛应用于内存管理、网络、数据压缩、DSP和数据库等领域。由于处理的信息量越来越大,现代BCAM应用需要更大的搜索空间。然而,fpga中传统的BCAM方法存在存储效率低下的问题。本文提出了一种利用fpga中标准SRAM块构建深、窄bcam的新颖高效技术。这种技术对于深和窄的凸轮是最有效的,因为BRAM消耗是模式宽度的指数。使用Altera公司的Stratix V设备,传统方法可以实现高达64k次的BCAM,而该技术可以实现高达4M次的BCAM。对于64k条目的测试用例,传统方法消耗43倍的alm,只达到Fmax的三分之一。一个完全参数化的Verilog实现是可用的。这个实现已经使用Altera的工具进行了广泛的测试。
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Deep and narrow binary content-addressable memories using FPGA-based BRAMs
Binary Content Addressable Memories (BCAMs) are massively parallel search engines capable of searching the entire memory space in a single clock cycle. BCAMs are used in a wide range of applications, such as memory management, networks, data compression, DSP, and databases. Due to the increasing amount of processed information, modern BCAM applications demand a deep searching space. However, traditional BCAM approaches in FPGAs suffer from storage inefficiency. In this paper, a novel and efficient technique for constructing deep and narrow BCAMs out of standard SRAM blocks in FPGAs is proposed. This technique is most efficient for deep and narrow CAMs since the BRAM consumption is exponential to pattern width. Using Altera's Stratix V device, traditional methods achieve up to 64K-entry BCAM while the proposed technique achieves up to 4M entries. For the 64K-entry test-case, traditional methods consume 43 times more ALMs and achieves only one-third of the Fmax. A fully parameterized Verilog implementation is available1. This implementation has been extensively tested using Altera's tools.
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