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An Efficient Hierarchical Banking Structure for Algorithmic Multiported Memory on FPGA

机译:FPGA上算法多端口存储器的高效分层存储结构

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Algorithmic multiported memory supports concurrent accesses by cooperating block RAMs (BRAMs) with algorithmic operations, and demonstrates the better performance per resource usage on FPGA when compared with register-based designs. However, the current approaches still use significant amount of FPGA resources and pose great design challenges when increasing the access ports. This paper proposes HB-NTX with a resource efficient hierarchical banking structure for nontable-based multi-ported memory design on FPGA. The regular design style enables a systematic flow to scale both read and write ports. When compared with the previous approaches, HB-NTX can reduce 62.03% BRAMs when composing a 2R4W memory with 32K depth. This paper further extends the HB-NTX to alleviate the complexity of the table-based memory designs. When compared with the previous table-based TBLVT approach, the proposed design for a 2R4W memory with 8K depth attains the cost reduction of 39.9%, 14.3%, and 15.6%, for registers, lookup tables, and BRAMs, respectively.
机译:算法多端口存储器通过将Block RAM(BRAM)与算法操作配合使用来支持并发访问,并且与基于寄存器的设计相比,FPGA上的每资源使用性能更好。但是,当前的方法仍然使用大量的FPGA资源,并且在增加访问端口时提出了巨大的设计挑战。本文针对FPGA上基于非表的多端口存储器设计提出了一种具有资源高效的分层存储结构的HB-NTX。常规的设计风格使系统的流程可以扩展读写端口。与以前的方法相比,HB-NTX在组成32K深度的2R4W存储器时可以减少62.03%的BRAM。本文进一步扩展了HB-NTX,以减轻基于表的内存设计的复杂性。与以前的基于表的TBLVT方法相比,针对8K深度的2R4W存储器的拟议设计分别将寄存器,查找表和BRAM的成本降低了39.9%,14.3%和15.6%。

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