A Cost-Effective FPGA-Based Approximate Multiplier for Machine Learning Acceleration
Author:
Affiliation:
1. COMSATS University Islamabad,Department of Electrical and Computer Engineering,Abbottabad Campus,Abbottabad,Pakistan
2. INRS University,Énergie Matériaux Télécommunications Research Centre,Montreal,Canada
Funder
Mitacs
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10391286/10391102/10391619.pdf?arnumber=10391619
Reference22 articles.
1. Approximate Arithmetic Circuits: A Survey, Characterization, and Recent Applications
2. A Survey on Approximate Multiplier Designs for Energy Efficiency: From Algorithms to Circuits
3. Energy-Efficient Approximate Multiplication for Digital Signal Processing and Classification Applications
4. TOSAM: An Energy-Efficient Truncation- and Rounding-Based Scalable Approximate Multiplier
5. A low-power high-speed accuracy-controllable approximate multiplier design
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