The systolic array genetic algorithm, an example of systolic arrays as a reconfigurable design methodology

I. Bland, G. Megson
{"title":"The systolic array genetic algorithm, an example of systolic arrays as a reconfigurable design methodology","authors":"I. Bland, G. Megson","doi":"10.1109/FPGA.1998.707907","DOIUrl":null,"url":null,"abstract":"We have designed and constructed a genetic algorithm engine using a systolic design methodology. The approach has a number of advantages. Firstly the design processes is systematic. A C source code version of the algorithm is used as a starting point and progressively the code is re-written into a form from where systolic cells can be designed. Secondly the modular nature of the arrays allow easy expansion of the design for different requirements (larger populations in this example). Hardware designs are re-used extensively and, in combination with reconfigurable computing techniques, can be swapped in or out on an application specific basis to construct arrays of the correct size. This can also be extended to swapping in and out whole elements of the macro-pipeline so that alternative operators, such as Tournament Selection can be employed. Thirdly, a traditional benefit of systolic arrays applies. The resultant design is massively parallel and significant throughput can be achieved.","PeriodicalId":309841,"journal":{"name":"Proceedings. IEEE Symposium on FPGAs for Custom Computing Machines (Cat. No.98TB100251)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE Symposium on FPGAs for Custom Computing Machines (Cat. No.98TB100251)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPGA.1998.707907","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

Abstract

We have designed and constructed a genetic algorithm engine using a systolic design methodology. The approach has a number of advantages. Firstly the design processes is systematic. A C source code version of the algorithm is used as a starting point and progressively the code is re-written into a form from where systolic cells can be designed. Secondly the modular nature of the arrays allow easy expansion of the design for different requirements (larger populations in this example). Hardware designs are re-used extensively and, in combination with reconfigurable computing techniques, can be swapped in or out on an application specific basis to construct arrays of the correct size. This can also be extended to swapping in and out whole elements of the macro-pipeline so that alternative operators, such as Tournament Selection can be employed. Thirdly, a traditional benefit of systolic arrays applies. The resultant design is massively parallel and significant throughput can be achieved.
收缩阵列遗传算法,收缩阵列作为可重构设计方法的一个例子
我们已经设计和构建了一个遗传算法引擎使用收缩设计方法。这种方法有很多优点。首先,设计过程是系统化的。该算法的C源代码版本被用作起点,并逐渐将代码重写为可以设计收缩细胞的形式。其次,阵列的模块化特性允许轻松扩展设计以满足不同的需求(在本例中为更大的人口)。硬件设计被广泛重用,并且结合可重构计算技术,可以在特定应用程序的基础上进行交换,以构建正确大小的数组。这也可以扩展到交换宏管道的整个元素,以便可以使用其他操作符,例如Tournament Selection。第三,收缩阵列的传统优势依然存在。由此产生的设计是大规模并行和显著的吞吐量可以实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信