Using integer linear programming for correctly rounded multipartite architectures

Orégane Desrentes, F. D. Dinechin
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Abstract

This article introduces several improvements to the multipartite method, a generic technique for the hardware implementation of numerical functions. A multipartite architecture replaces a table of value with several tables and an adder tree. Here, the optimization of multipartite tables is formalized using Integer Linear Programming so that generic ILP solvers can be used. This improves the quality of faithfully rounded architectures compared to the state of the art. The proposed approach also enables correctly rounded multipartite architectures, providing errorless table compression. This improves the area by a factor 5 without any performance penalty compared with the state of the art in errorless compression. Another improvement of the proposed work is a cost function that attempts to predict the total cost of an architecture in FPGA architectural LUTs, where most of the previous works only count the size of the tables, thus ignoring the cost of the adder tree.
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用整数线性规划求解正确四舍五入的多部结构
本文介绍了对多部法的改进,多部法是一种用于数值函数硬件实现的通用技术。多部分架构用几个表和一个加法器树代替一个值表。在这里,使用整数线性规划形式化了多部表的优化,以便可以使用通用的ILP求解器。与现有技术相比,这提高了忠实圆形架构的质量。所提出的方法还支持正确的四舍五入的多方架构,提供无差错的表压缩。与目前的无差错压缩技术相比,这在没有任何性能损失的情况下将面积提高了5倍。所提出的工作的另一个改进是成本函数,它试图预测FPGA体系结构lut中的体系结构的总成本,其中大多数先前的工作只计算表的大小,从而忽略了加法树的成本。
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