Graph neural networks and their application in the design of digital VLSI
Abstract
The article discusses the method of machine learning on graphs, presents the architecture of modern graph neural networks, as well as their application for solving digital VLSI design problems, especially in placing standard cells at the layout design stage. The solution of this problem using machine learning methods is an urgent problem, since the standard placement algorithms used in modern CAD systems face difficulties when working with digital circuits, the number of logic elements in which reaches 106 and more. This leads to a long operating time and non-optimality of the results obtained in terms of the occupied area and power consumption of the designed VLSI.
About the Authors
N. V. Zheludkov
ФГУ ФНЦ НИИСИ РАН
Russian Federation
Russian Federation
K. A. Petrov
ФГУ ФНЦ НИИСИ РАН
Russian Federation
Russian Federation
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Review
For citations:
Zheludkov N.V., Petrov K.A. Graph neural networks and their application in the design of digital VLSI. МАТЕМАТИЧЕСКОЕ И КОМПЬЮТЕРНОЕ МОДЕЛИРОВАНИЕ СЛОЖНЫХ СИСТЕМ: ТЕОРЕТИЧЕСКИЕ И ПРИКЛАДНЫЕ АСПЕКТЫ. 2022;12(4):61-67. (In Russ.)
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