在现场可编程门阵列上用快速梯度法求解二次规划的结构

Marc-Alexandre Boechat, Junyi Liu, Helfried Peyrl, A. Zanarini, T. Besselmann
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引用次数: 16

摘要

本文提出了一种在现场可编程门阵列(FPGA)上实现梯度优化方法的体系结构。将基于梯度的算法优势与定制FPGA实现的计算优势相结合,可以解决例如在微秒范围内的模型预测控制(MPC)应用中出现的二次程序。实验比较表明,与并行软件版本相比,所提出的FPGA实现具有一到两个数量级的计算优势。提出的基于fpga的解决方案可以扩大MPC的适用性,直到最近几年才被认为是遥不可及的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An architecture for solving quadratic programs with the fast gradient method on a Field Programmable Gate Array
In this paper an architecture for the implementation of gradient-based optimisation methods on a Field Programmable Gate Array (FPGA) is proposed. Combining the algorithmic advantages of gradient-based algorithms with the computational strengths of a tailored FPGA implementation allows to solve quadratic programs occurring, for example, in Model Predictive Control (MPC) applications in the microsecond range. The experimental comparisons show a computational advantage of the proposed FPGA implementation against parallel software versions ranging between one and two orders of magnitude. The proposed FPGA-based solution can broaden the applicability of MPC to problems that were considered out-of-reach till recent years.
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