文章基本信息

标题：Automatical implementation of artificial neural networks on hardware
其他标题：Yapay sinir ağlarının otomatik olarak donanım ortamında gerçeklenmesi
本地全文：下载
作者：Namık Kemal Sarıtekin ; İbrahim Şahin
期刊名称：Sakarya University Journal of Science
印刷版ISSN：1301-4048
电子版ISSN：2147-835X
出版年度：2016
卷号：20
期号：2
DOI：10.16984/saufenbilder.28619
语种：English
出版社：Sakarya University
摘要：While Artificial Neural Networks (ANNs) are implemented on FPGAs, first, a logic design is made for the desired ANN. Second, this design is coded in a hardware description language and is synthesized for a target FPGA chip. These procedures are time consuming, error prune processes and requires expert personal. In this study, an ANN data paths design tool (YTA) was developed to help automate the application of ANNs to FPGAs, to reduce the design and implementation time, and to minimize the expert requirements while mapping ANNs to FPGAs. YTA was tested with several test cases successfully. Using YTA, data paths can be designed and HDL codes can be produced automatically for given ANN in seconds.
其他摘要：Yapay Sinir Ağları (YSA) FPGA tabanlı sistemlerde gerçeklenirken; öncelikle istenen YSA için bir sayısal tasarım yapılır, ardından yapılan tasarım, bir donanım tanımlama dilinde kodlanarak hedef FPGA için sentezlenir. Bu işlemler zaman alan, uzman gerekti
关键词：design automation;FPGA;HDL;artificial neural networks
其他关键词：tasarım otomasyonu;FPGA;HDL;yapay sinir ağı