A Graph Neural Network Model for Fast and Accurate Quality of Result Estimation for High-Level Synthesis

A Graph Neural Network Model for Fast and Accurate Quality of Result Estimation for High-Level Synthesis

High-level synthesis (HLS) is a solution for rapid prototyping of application-specific hardware using the C/C++ behavioral programming language. Designers can apply HLS directives to optimize hardware implementations by making trade-offs between cost and performance. However, c...

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Bibliographic Details
Main Authors: M. Usman Jamal, Zhuowei Li, Mihai T. Lazarescu, Luciano Lavagno
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Electronic design automation (EDA)
graph neural network (GNN)
machine learning (ML)
high-level synthesis (HLS)
quality of results (QoR)
field-programmable gate array (FPGA)
Online Access:https://ieeexplore.ieee.org/document/10213402/

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https://ieeexplore.ieee.org/document/10213402/

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