Implementation of LS-SVM with HLS on Zynq

Ma Ning, Wang Shaojun, Pang Yeyong, Peng Yu
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引用次数: 7

Abstract

In recent years, implementing a complicated algorithm in an embedded system, especially in a heterogeneous computing system, has gained more and more attention in many fields. The problem is that the implementation needs amounts of coding and debugging work, even if the algorithm has been verified by high-level language in PC environment. Our demo presents a method which can reduce the time of developing an algorithm in an embedded and heterogeneous system by high level synthesis method. Least Square Support Vector Machine(LS-SVM) algorithm was realized on Zynq platform by translating high-level language to Hardware Description Language(HDL). Basing on the feature of the developed heterogeneous system and the theory of LS-SVM, three parts were implemented to realize LS-SVM which includes a generating Kernel Matrix module, a solving linear equations module and a forecasting module. The first and the third parts have been placed in ARM processor by C language. Moreover, considering that the second parts was compute-intensive, it has been realized in logic resource by using high-level language. To manage data communication and computing task, an SOPC system has been designed on Zynq platform which worked in PXI chassis. Experiments demonstrate that the design method is feasible and can be used for the implementation of other complicate algorithm. The precision and time consumption in computing are given at the end.
基于HLS的LS-SVM在Zynq上的实现
近年来,在嵌入式系统中,特别是在异构计算系统中实现复杂的算法越来越受到许多领域的关注。问题是,即使该算法在PC环境中经过高级语言的验证,其实现也需要大量的编码和调试工作。本演示提出了一种采用高级综合方法减少嵌入式异构系统中算法开发时间的方法。最小二乘支持向量机(LS-SVM)算法在Zynq平台上通过将高级语言转换为硬件描述语言(HDL)实现。根据已开发异构系统的特点,结合LS-SVM理论,实现了核矩阵生成模块、线性方程求解模块和预测模块三部分的LS-SVM实现。第一部分和第三部分用C语言编写在ARM处理器上。另外,考虑到第二部分的计算量较大,采用高级语言在逻辑资源上实现。为了实现对数据通信和计算任务的管理,在PXI机箱中工作的Zynq平台上设计了一个SOPC系统。实验表明,该设计方法是可行的,可用于其他复杂算法的实现。最后给出了计算精度和时间消耗。
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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