DT2CAM: A Decision Tree to Content Addressable Memory Framework

Decision trees are powerful tools for data classification. Accelerating the decision tree search is crucial for on-the-edge applications with limited power and latency budget. In this paper, we propose a content-addressable memory compiler for decision tree inference acceleration. We propose a novel...

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Veröffentlicht in:	IEEE transactions on emerging topics in computing 2023-07, p.1-6
Hauptverfasser:	Rakka, Mariam, Fouda, Mohammed E., Kanj, Rouwaida, Kurdahi, Fadi
Format:	Artikel
Sprache:	eng
Schlagworte:	Associative memory Codes Decision Tree Decision trees Encoding Hardware acceleration Hardware Compiler Machine Learning Synthesizer Synthesizers Table lookup Ternary Content Addressable Memory
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