RoCoCo: Row and Column Compression for high-performance multiplication on FPGAs

H. F. Ugurdag, O. Keskin, Cihan Tunc, F. Temizkan, G. Fici, Soner Dedeoglu
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引用次数: 11

Abstract

Multiplication is, in no doubt, one of the top few frequently used operations in hardware and software. In high-performance hardware design, after high-level optimizations are exhausted, component level optimizations are employed such as building fast multipliers. Most fast multiplier architectures use some form of a Carry Save Adder (CSA) Tree, which is also called Column Compression (CC). We propose a new CC method called RoCoCo (Row and Column Compression), which also compresses the tree along rows so that the final adder is small and fast. Although CC results in faster multipliers in ASIC implementations, it is an assumption by designers that they are not the wisest choice on FPGAs. On the contrary, we were able to show through Xilinx synthesis results that RoCoCo (and sometimes Dadda CC) frequently offer faster multipliers than the built-in implementation of the multiply operation in Xilinx ISE synthesis tool.
RoCoCo:用于fpga上高性能乘法的行和列压缩
毫无疑问,乘法是硬件和软件中最常用的几个操作之一。在高性能硬件设计中,在高级优化耗尽后,采用组件级优化,如构建快速乘法器。大多数快速乘法器架构使用某种形式的进位保存加法器(CSA)树,也称为列压缩(CC)。我们提出了一种新的CC方法,称为RoCoCo(行和列压缩),它也沿着行压缩树,使最终的加法器小而快。虽然CC在ASIC实现中导致更快的乘法器,但设计人员假设它们不是fpga上最明智的选择。相反,我们能够通过Xilinx合成结果显示,RoCoCo(有时是Dadda CC)通常比Xilinx ISE合成工具中内置的乘法操作实现提供更快的乘法运算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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