基于遗传算法的Vivado HLS硬件加速  

Vivado High Level Synthesis Hardware Acceleration Based on Genetic Algorithm

作　　者：陈宝林 黄晞[1] 张仕[2] 郭升挺 吴家飞 苏浩明 

机构地区：[1]福建师范大学医学光电科学与技术教育部重点实验室福建省光子技术重点实验室,福州350007 [2]福建师范大学数学与计算机科学学院,福州350117

出　　处：《计算机系统应用》2018年第1期120-126,共7页Computer Systems & Applications

基　　金：福建省科技厅工业高校产学合作项目(2013H6008)

摘　　要：为适应当前"大数据+深度模型"时代的到来,利用FPGA进行各种算法的硬件加速为其提供了一种可行的解决方案.本文利用Vivado HLS工具,基于遗传算法设计了一套智能硬件加速架构,编程实现自动生成tcl文件、自动调用HLS工具完成仿真和提取报表中的数据进行分析,并对Xilinx公司所给的FIR和DCT等案例程序进行了测试.实验中寻找到了较优的解决方案,效率相比人工不断尝试的方法有了数量级的提升,满足了当前一般算法在硬件加速的通用性.At present, in order to adapt to the coming of＂big data and in-depth model＂ age, a feasible solution is put forward by using FPGA to realize hardware accelerator of various algorithms. In this study, by using Vivado HLS tools, a set of intelligent hardware acceleration architecture is designed based on the genetic algorithm, which can automatically generate TCL file by programming, and automatically call HLS tool to complete the simulation analysis and extract the data to analyze in the report. What＇s more, the case programs like FIR and DCT given by the Xilinx company are tested. A better solution is found in the experiments, and the efficiency is increased by magnitude compared with the manual methnds. It has met the universality of the general algorithm in hardware acceleration.

关 键 词：现场可编程门阵列 加速 遗传算法 高层次综合 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]