AxOMaP: Designing FPGA-based Approximate Arithmetic Operators using Mathematical Programming

With the increasing application of machine learning (ML) algorithms in embedded systems, there is a rising necessity to design low-cost computer arithmetic for these resource-constrained systems. As a result, emerging models of computation, such as approximate and stochastic computing, that leverage...

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Veröffentlicht in:	ACM transactions on reconfigurable technology and systems 2024-06, Vol.17 (2), p.1-28, Article 31
Hauptverfasser:	Sahoo, Siva Satyendra, Ullah, Salim, Kumar, Akash
Format:	Artikel
Sprache:	eng
Schlagworte:	Arithmetic and datapath circuits Circuit optimization Computing methodologies Hardware Hardware accelerators Randomized search Software tools for EDA
Online-Zugang:	Volltext
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