Robust GNN-Based Representation Learning for HLS

The efficient and timely optimization of microarchitecture for a target application is hindered by the long evaluation runtime of a design candidate, creating a serious burden. To tackle this problem, researchers have started using learning algorithms such as graph neural networks (GNNs) to accelera...

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Veröffentlicht in:	Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design S. 1 - 9
Hauptverfasser:	Sohrabizadeh, Atefeh, Bai, Yunsheng, Sun, Yizhou, Cong, Jason
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 28.10.2023
Schlagworte:	Adaptation models Computational modeling Microarchitecture Representation learning Runtime Systematics Transfer learning
ISSN:	1558-2434
Online-Zugang:	Volltext
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